iisc physics phd students

Inorganic and Physical Chemistry

Indian institute of science, bangalore.

iisc physics phd students

2022-23 PhD Admissions

The IPC department is participating in the PhD admissions for the 2022-23 academic year. The deadline for applications is 22 nd March 2022 . Further details may be found here: IISc's main admission site . Also consult the page on important dates .

Information on Admission to the Regular and Integrated PhD Programmes

This page provides quick information regarding admission to the PhD programmes at IPC department and is meant to supplement the information given in IISc's main admission site . The important dates are given here .

NOTE: All applications must be submitted only through the portal at IISc's admission site (link above).

Regular PhD and Integrated PhD programmes

The IPC department accepts students into two PhD programmes, viz. regular and integrated PhD programmes.

The Regular PhD programme is a post-Master's degree programme, and has a typical duration of 5 years. Once the admitted students join a research group, they begin their work under the guidance of their research advisor. They also undergo several courses as part of their research training programme.

The Integrated PhD programme is a post-Bachelor's degree programme, and has a typical duration of 6 years. Students are admitted into the Division of Chemical Sciences. For the first two years, the students take Master's level courses, with a project in fourth semester. By the start of the third semester, the students join a research group either in IPC or in another Chemistry department.

Research Fields

Required qualifications.

Master's degree in Science with Second Class or higher in any discipline.

       OR

Master's degree in Engineering with Second Class or higher in one of the following disciplines: Chemical Engg., Materials Engg., Biomaterials Engg., Biotechnology or Nanotechnology.

Note : The Second Class requirement applies to candidates in the General / OBC category. It is relaxed to Pass Class for SC / ST candidates.

  • List of valid examinations: Valid GATE (Chemistry), Joint CSIR-UGC NET for JRF, CSIR NET for JRF, JEST (Physics) qualification certificate, valid INSPIRE Fellowship.

Bachelor of Science in Chemistry

Application, Interview, and Selection Process

Candidates must submit their application only via the online form at the main IISc admission's website. See the top of this webpage for the link to the site.

At the time of the application, the candidate must choose to apply to the IPC department. Two other departments in IISc may also be given as a choice.

Candidates will be invited to an interview in the IPC department based on a cut-off mark/rank in the qualifying examination. See the Required Qualifications section of this page for the list of examinations.

The interview is mandatory . Candidates who do not attend the interview automatically forfeit their chance for admission.

The interviews for August term admissions typically take place between mid May or early June. Interviews for the January term (mid-year) admissions, if conducted, typically take place in the second half of November.

Candidates will be invited to an interview based on their JAM rank. This will be independent of the automatic preference-based allotment process followed by the JAM on behalf of participating institutes.

The interviews are usually conducted around the second half of May.

Offer of Admission

Contact regarding admissions.

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Welcome to etd@IISc!

This is the digital repository of Theses and Dissertations of Indian Institute of Science , Bangalore, India. You can search, browse and access theses and dissertations from this collection. This repository has been developed to capture, disseminate and preserve research theses of Indian Institute of Science. It complements ePrints@IISc , the research publications repository of IISc

Note that only recently completed M.Sc.(Engineering) and Ph.D. theses will be accepted for online submission to etd@IISc. Further, only research student or her/his guide can submit the thesis. IISc Library is converting old print theses for adding to etd@IISc. For submitting electronic copy of an old theses, please contact the etd@IISc Administrator .

Before you can submit a thesis, you should first Register with etd@IISc. After completing registration, you can proceed to submit your thesis. Only IISc email ID will be accepted for registration.

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Research Admissions Aug 2023

Visit the link for the provisional list of candidates recommended by the department.

Lab Prefamiliarization Slides

Lab Prefamiliarization Video Recording

The admission process for the Aug 2023 cycle to the Department of Computational and Data Sciences (CDS) comprises two phases. Phase I will be an online aptitude test on the HackerEarth platform, which serves as the first part of the evaluation and Phase II will be an in-person oral interview for all candidates who qualified in the aptitude test conducted in Phase I.

Candidates shortlisted for the online aptitude test (Phase I of the interview) will receive a call letter or email from the IISc Admissions office (please login to the IISc admissions portal and check for the call letter). The online aptitude test will be conducted on the same day and session as per the allotted slot in your call letter. The test will be held in the CDS department and you will be provided with a computer to take the test (you need not bring a laptop/computer). You will receive a separate email from the CDS department for your test and instructions such as the test link, rules, guidelines, practice test, etc. This online aptitude test will have multiple-choice and programming questions as per the syllabus below.

The Phase II in-person oral interview is only for students who attempt and qualify in the online aptitude test conducted in Phase I. The syllabus for the interview (similar to the aptitude test, with lab-specific readings) is also given in detail below.

The shortlisted candidates for the online aptitude test have been sent an email from the CDS department to fill out an online student information Google form. This must be completed and submitted to participate in the in-person online aptitude test and interview. As part of this, candidates should choose up to three labs for which they will be considered. These labs are described below.

Online Aptitude Test

The Phase I online objective and programming test will be conducted using the “HackerEarth” online platform on the same day and session as per the allotted slot in your call letter. This test will be held in the CDS department, and the candidates will be provided with a computer to take the online exam . Candidates will be emailed with a link to the online test a few days before the test date. The test will be enabled at the start of your session before the in-person interviews begin. It must be completed in a single sitting. You will need to create a free HackerEarth account to take the test. You MUST use the same email address as the one used for your IISc Admissions Application. Please do this ahead of time. That email will also have another link to let you take a practice test to get familiar with the HackerEarth platform. These practice questions are not from the test syllabus. Candidates may take the practice test as many times as they want. Candidates should get familiar with the programming IDE, compilation, and testing interface of HackerEarth to ensure that the programming questions are correctly attempted.

The online aptitude test will have 8 questions. There will be 6 multiple choice questions (5 marks each) and 2 programming questions (25 marks each). The topics for the objective test are:

  • Combinatorics, Linear Algebra/Matrices, Probability and Statistics, Differential Equations, Plotting, Data Structures and Algorithms.

The programming languages that you can use are C, C++ and Java . The HackerEarth interface will allow you to type the program, compile it and run test cases, all within the browser. We will provide a basic code template for reading and writing the inputs and outputs for each problem. The candidates should focus on the actual code logic and brush up on concepts such as if/then/else conditions, for/while loops and arrays/data structures.

Sample questions from previous year tests are available here .

Students are encouraged to first solve the problems that they are comfortable with and then move on to more difficult problems.

In-Person Oral Interview

Students who qualify in the online aptitude test (Phase I of the interview) will only attend the in-person oral interview (Phase II of the interview) in the allotted slot as per the call letter. In the oral interview, you will be questioned on the following basic topics, and on advanced topics that are based on your lab preferences:

Basic Topics : Linear Algebra; Probability & Statistics; Programming, Data Structures, Algorithms; Ordinary Differential Equations; Discrete Mathematics.  Final year undergraduate level preparation is required.

Advanced Topics: You will be questioned on the topics related to labs selected in the student information Google form. The topics for each lab and the prior training expected are listed below. Candidates choosing a lab must be prepared on at least one of the lab-related interview topics.

Note: Most labs give preference to applicants for the Ph.D. program over the M.Tech. (Research) program. Some labs may not even take any students for the M.Tech. (Research) program. Students with a B.E./B.Tech degree are also eligible to apply for the Ph.D. program

Candidates should prepare well on their fundamentals, come with a focus and knowledge of the research areas they would like to target in their PhD, and have clarity on the preferred lab(s) and the kind of work done in them. Review the research topics and the papers from the labs you are interested in.

List of labs that are admitting students in Aug 2023

The following labs (ATCG, BioMedIA, BCL, CSPL, FLAME, MATRIX, NATL, STARS) accept students from all background qualifications

1. Algorithmic Techniques for Computational Genomics (ATCG)

Faculty: Chirag Jain

Website: https://at-cg.github.io

Lab Description: We work at the intersection of computer science and biology to accelerate scientific discovery by designing novel algorithms, data structures and open-source software tools. We address computational problems associated with analysis of DNA and RNA sequences. Refer to the lab website to learn more about ongoing projects.

Interview topics: Algorithms design and analysis, data structures, graph algorithms

Prior training: Any degree. Strong programming and algorithm development skills are required.

2. Biomedical Image Analysis (BioMedIA) Lab

Faculty : Vaanathi Sundaresan

Website : https://cds.iisc.ac.in/faculty/vaanathi/biomedia/index.html

Lab Description : Our aim is to develop innovative AI-based methods for computational analysis of multidisciplinary biomedical images for clinical applications. We specifically focus on building scalable and translatable tools for big data applications in neuroimaging. We are also interested in tackling key challenges of medical image analysis including label scarcity and data diversity, model generalisability and interpretability.

Our current research areas include computer vision and machine learning-based methods for identification of MR imaging biomarkers for various neurological diseases and their population-level impact, semi-supervised techniques for analysis of various imaging modalities, data harmonisation/domain adaptation, image reconstruction and quality improvement.

Interview topics: Signal Processing, Image Processing, Linear Algebra, Probability and Machine Learning basics.

Prior Training : We are looking for students with an engineering background, preferably Computer Science or Electrical Engineering, interested in the following topics: deep learning and computer vision applications, domain adaptation and weakly supervised learning, uncertainty estimation and explainable AI methods in medical imaging, specifically neuroimaging.

3 . Biomolecular Computation Laboratory (BCL)

Faculty : Debnath Pal

Website: https://cds.iisc.ac.in/faculty/dpal/    

Lab description: The aim of the lab is to understand biological data for insights into biological structure, function and processes at multiple scales. The scope of work spans the areas of genomics, proteomics, metabolomics, structural biology, health and disease, methods and algorithms. There is an opportunity to do research problems in real-life projects in cancer, diabetes, neurodegeneration etc., where intensive bio-computational analysis is required.

For the Aug 2023 admissions, we are looking for two PhD students to work in the broad areas of health and disease which may involve translational components.

Interview topics : Students are expected to have good programming knowledge and a sound understanding in at least one of the basic subjects at the undergraduate level: Math, Physics or Chemistry. Exposure to data science, bioinformatics and computational biology is desirable but not essential.

Prior training: Students with sound knowledge in any background and enthusiasm for learning biology.

4 . Computational & Statistical Physics Lab (CSPL)

Faculty: Murugesan Venkatapathi

Website: https://cds.iisc.ac.in/faculty/murugesh/    

Lab description: Research at CSPL can be broadly grouped into a) theoretical and computational models in condensed matter, b) numerical and scientific computing, c) randomized algorithms and statistical computing, and d) statistical models and data analysis. Typically, PhD students work in one of the three areas a, b or c.

For the Aug 2023 admissions, CSPL is looking for two PhD students to work in the broad areas ‘a’ and ‘c’. In the former, we would like to extend some of our recent understanding of counterintuitive optical properties of extremely small metal nanoparticles to their electrical properties as well. In ‘c’, we are interested in developing new algorithms for randomized numerical linear algebra.

Interview topics : Linear/Matrix algebra, numerical methods, statistics, topics in physics

Prior training: A degree in Engineering or Physics or Mathematics as appropriate for the research topic.

5. FLAME:Lab (FLow Analysis and Multi-physics simulations at Extreme-scale) Lab

Faculty: Konduri Aditya

Website: https://cds.iisc.ac.in/faculty/konduriadi/ and https://flamelab-iisc.github.io

Lab description: The research group focuses on the simulation and analysis of multi-scale multi-physics fluid flow problems that leverage high performance computing (HPC) platforms. Specifically, the work would involve development of HPC centric numerical methods and algorithms for solving partial differential equations (PDE) that are relevant to computational fluid dynamics (CFD), application of machine learning methods to analyze and model data generated from simulations, and investigation of turbulent flow problems that arise in combustion systems (gas turbine and scramjet engines), high-speed aerodynamics and environmental flows. 

Our current projects include reduced-order modelling (ROM) for reacting flows, scalable asynchronous PDE solvers, hydrogen combustion, and detection & forecasting of extreme events.  For the Aug 2023 admissions, we are looking for three PhD/MTech (Research) students.

Interview topics: Numerical methods, linear algebra, probability, scientific programming, differential equations, fluid mechanics (optional), programming models (optional)

Prior training:  Students should have a Bachelors’ or Masters’ degree in any one of the following areas: Mechanical Engineering, Aerospace Engineering, Chemical Engineering, Computational Engineering, Computational Physics, Applied Mathematics, Scientific computing or similar areas. Ph.D. candidates are preferred.

6. MATRIX:Lab  (Materials-physics & Algorithmic Techniques Research In eXtreme-computing) Lab

Faculty:  Phani Motamarri

Website: https://cds.iisc.ac.in/faculty/phanim/    

Lab description: The research in the lab is centered around developing mathematical techniques leading to scalable computational and data-driven methodologies that are aimed at accelerating materials discovery.  The key goal is to push the boundaries of the current predictive capabilities of materials design using quantum mechanical theories opening up the possibility of addressing a broad range of scientifically and technologically important problems that have been out of reach so far. Application areas include the design of energy storage materials, catalytic materials, quantum modeling of complex defects in functional and structural materials, multi-scale modeling in combustion and nano-fluidic applications.

In Aug 2023 admissions, MATRIX lab is looking for bright and highly motivated research students to join our lab. We are looking for candidates interested in conducting highly interdisciplinary research cutting across applied mathematics, quantum mechanics, materials science, solid mechanics, finite-element methods, numerical linear algebra, machine learning and hardware-aware large-scale scientific computing on multinode CPU and GPU architectures (MPI+CUDA). This is an exciting opportunity for students trained in traditional streams of science and engineering to conduct multidisciplinary research in the cutting-edge areas of computational science and data science, thereby acquiring transferable skills.

Interview topics : Numerical methods, Linear Algebra, Calculus, Scientific Programming, Differential equations, Topics based on student’s UG/PG background. (for eg: Solid Mechanics, Quantum Physics, Computational Materials, Finite-element methods etc.,)

Prior training: Bachelors’ or a Masters’ degree in any one of the following areas: Mechanical Engineering, Materials Engineering, Chemical Engineering, Computational Engineering, Physics, Applied Mathematics Scientific computing or similar areas. Strong programming skills are a must

7. Numerical Algorithms and Tensor Learning Laboratory (NAT Lab)

Faculty: Ratikanta Behera

Website: https://cds.iisc.ac.in/faculty/ratikanta/lab.html

Lab Description: We are developing adaptive recurrent neural networks to solve time-varying tensor equations. The aim is to design innovative, scalable, and efficient tensor-based algorithms supported by theoretical principles to solve significant existing and emerging multidimensional problems. Specifically, interested in developing fast tensor algorithms for solutions to multilinear systems, nonlinear optimization problems, low-rank approximation, generalized inverses of tensors, and solutions to partial differential equations in high dimensions problems. We also focus on developing HPC-centric adaptive wavelet algorithms for solving Partial Differential Equations (PDEs), Fractional Differential Equations (FDEs), integral equations, and signal & image processing.

Interview Topics: Linear/Matrix algebra, Numerical Methods, Differential Equations with Basic Programming.

Student Background: Mathematics is preferable. However, we welcome applicants with Physics, Computer Science, Earth Science, Information Technology, Electrical, Electronics and/or Communications, or any other closely related areas who are enthusiastic about learning and developing skills in these areas.

For the 2023 Admissions cycle, the NAT Lab is looking for 2-3 enthusiastic students interested in the following topic.

  • Tensor Decompositions and Approximations
  • Generalized inverses for Matrix/Tensor
  • Neural Networks and its Applications
  • Image/Video Processing
  • Wavelet Methods for (Ordinary/Partial/Fractional) Differential Equations
  • Wavelets in Scientific Computing

8. Scientific Machine Learning and Operations (STARS)

Faculty: Sashikumaar Ganesan

Website: https://cds.iisc.ac.in/news/people/sashikumaar-ganesan/    

Lab description: Scientific Machine Learning (ScML) has the potential to revolutionize how we solve partial differential equations (PDEs). However, realizing this potential requires overcoming several challenges. Our research group is focused on addressing these challenges and making ScML a widely used tool in scientific computing. 

Our research plan includes improving the generality and computational efficiency of Neural Networks, as well as addressing time-dependence handling, and dynamic boundary and interior layer handling. We will also incorporate Finite Element Methods, MLOps, and digital twin techniques to enhance efficiency, scalability, and reliability. 

Furthermore, we plan to apply ScML schemes to computational fluid dynamics (CFD) to improve the accuracy of fluid flow simulations. Our ultimate goal is to transform our open source finite element package ParMooN into an open source ScML package, contributing substantially to scientific machine learning and revolutionizing how PDEs are solved.

Interview topics : Linear Algebra or Numerical Methods or Basics of Machine Learning or Parallel programming

Prior training: While prior knowledge of modeling, simulation, and programming is preferred, it is not required. We welcome applicants with any degree background who are enthusiastic about learning and developing skills in these areas.

The following labs (CSL, DREAM, MARS, NLP, VAL, VCL) only accept students from CS/EE background qualification.

1. Cloud Systems Lab (CSL)

Faculty: J. Lakshmi

Website: http://www.serc.iisc.ac.in/faculty/jlakshmi and http://www.serc.iisc.ac.in/faculty/jlakshmi/cloud-system-lab

Lab Description: Cloud Systems Lab (CSL) engages in large-scale distributed systems research, specifically in the emerging and evolving paradigms of service architectures, isolation, resource provisioning and management, virtualization, guarantees (QoS) for application performance, dependability, fault tolerance, etc. Incumbent students are required to have good background knowledge of Operating system topics like resource management, scheduling, process and memory management, disks, and file systems, I/O devices, interrupt management, networking, synchronization, deadlocks, agreement protocols, etc., and passion for systems research.

Current research work entails architecting and evaluating serverless platforms for QoS, realizing lightweight virtualization environment for real-time DAG based workflows, Service resilience using data-oriented recovery paradigms, Intelligent solutions for real-time dynamic optimal placement problems.

We are interested in, but not limited to, exploring disaggregated resources for distributed computing, stateful serverless paradigm, and software defined data centers.

Interview topics: Operating Systems, Distributed Systems, Computer Organization

Prior training: Students must have a Bachelors’ or Masters’ degree in Computer Science, Information Technology, Electrical, Electronics and/or Communications.

2. DREAM:Lab (Distributed systems Research on Emerging Applications & Machines)

Faculty: Yogesh Simmhan

Website: https://cds.iisc.ac.in/faculty/simmhan , http://www.dream-lab.in

Lab Description: Research in the DREAM:Lab focuses on distributed systems, Big Data platforms, scalable software platforms for ML, and distributed graph algorithms. We explore design and develop software platforms, data management architecutures and distributed algorithms for distributed systems like cloud computing, edge computing, accelerators and quantum computing, with applications to emerging domains like drones/UAVs, AR/VR, hyperledger and smart city/IoT.

For the 2023 Admissions cycle, the DREAM:Lab is looking for 3-4 enthusiastic students interested in:

  • Scalable platforms for federated deep learning using GPU-accelerated edge and cloud computing
  • ML-driven scheduling algorithms and software platforms for serverless multi-cloud computing
  • Platforms and algorithms for hybrid quantum computing and cloud computing
  • NoSQL and Big Data platforms for spatio-temporal and video data
  • Incremental and distributed algorithms for large streaming graphs in social netwoks and IoT
  • Scalable consensus algorithms and platforms for distributed hyperledgers and blockchain

Students must have strong aptitude and demonstrated skills in systems software, algorithms and programming.

Interview topics: Operating Systems (or) Graph Algorithms (or) Distributed Systems.

Recommended Reading:

  • Operating System Concepts by Silberschatz, Gavin and Gagne
  • Distributed Systems: Concepts and Design by Coulouris, et al.
  • In search of an understandable consensus algorithm, Diego Ongaro and John Ousterhout, USENIX ATC , 2014, https://www.usenix.org/node/184041
  • TiFL: A Tier-based Federated Learning System, Zheng Chai, et al, HPDC , 2020 https://arxiv.org/abs/2001.09249

Prior training: Students must have a Bachelors/Masters degree in Computer Science, Electrical, Electronics or Communications. Strong programming, algorithms and systems skills required. Ph.D. candidates preferred.

3. Middleware And Runtime Systems (MARS) Lab

Faculty: Sathish Vadhiyar

Website: https://cds.iisc.ac.in/faculty/vss

Lab Description: High performance computing (HPC), Parallel computing – middleware, system software, algorithms and applications on large-scale parallel computers and GPUs.

Some of the recent research topics in the MARS lab are the following.

  • Harnessing the power of both CPUs and GPUs in a hybrid manner in modern-day parallel systems.
  • Novel models of parallelism for Machine Learning (ML)/Deep Learning (DL) applications.
  • High performance parallel I/O solutions for scientific and ML/DL applications.
  • Communication-minimization strategies for Exascale applications including development of asynchronous methods, one-sided communications and approximate computing.
  • Identifying scalability bottlenecks in parallel applications and developing acceleration and scalability improvement techniques.
  • Fault tolerance frameworks for parallel scientific and ML/DL applications.

Interview topics:

  • Operating Systems including pthreads, filesystems.
  • Computer architecture including multi-core CPUs and modern GPUs, differences between shared memory and distributed memory parallel architectures, different network topologies (e.g., ring, mesh etc.)
  • MPI parallel programming interface – Google for “MPI Complete reference” and read Introduction, Point-to-Point and Collective Communications chapters.

Prior training: Students must have a Bachelors’ or Masters’ degree in Computer Science, Information Technology, Electrical, Electronics and/or Communications. Strong programming, algorithms and systems skills are required. Ph.D. candidates are preferred.

4. Natural Language Processing (NLP) Lab

Faculty: Danish Pruthi

Website: https://danishpruthi.com/

Lab Description: This new lab broadly works in the areas of Natural Language Processing (NLP) and Machine Learning (ML). These areas already impact our lives—from answering questions we ask, curating content we read online,  auto-completing words we are likely to type, to translating text from languages we don’t understand. The lab aims to ensure that such technologies are inclusive, safe and are adopted responsibly. Specifically, we plan to initiate projects related to inclusive model evaluation, model control (e.g., editing, de-biasing trained models) and also on validating data sources (in response to biased or harmful behavior). Additionally, we hope to contribute towards important NLP applications (e.g., content moderation, assisted writing), and engage in understanding their broader societal and ethical implications. From the outset, the lab is envisioned to be diverse, transparent, friendly and highly collaborative.   Interview topics: Language Modeling, Probability and basics of Machine Learning and Deep Learning.

Prior training: Students must have a Bachelors’ or Masters’ degree in Computer Science, Information Technology, Electrical, Electronics and/or Communications or other closely related disciplines.

5. Vision and AI Lab (VAL – formerly Video Analytics Lab)

Faculty: R. Venkatesh Babu

Website: http://val.cds.iisc.ac.in

Lab Description: At VAL, we aim to perform world-class research in the broad fields of Computer Vision and Machine Learning, to push the performance limits on different applications, and ensure their reliability in practical settings. Our research and expertise spans across several areas in Deep Learning for Computer Vision as listed below:

i) Representation Learning iii) Domain Adaptation iv) Adversarial Attacks and Defenses v) Self-supervised and unsupervised learning vi) Out-of-Distribution (OOD) Robustness of Deep Models/ Domain Generalization vii) Object Detection viii) Learning on long-tail data ix) Generative models x) 3D Vision xi) Multi-modal learning.

Interview topics: Linear Algebra, Probability, Basics of Machine Learning and Image Processing (optional)

Prior training: Students must have a Bachelor’s or Master’s degree in either Computer Science, Information Technology, Electrical, Electronics and/or Communications or in any other closely related areas.

6. Visual Computing Lab (VCL)

Faculty: Anirban Chakraborty

Website: http://visual-computing.in/

Lab Description: At VCL, we are interested in developing novel computer vision and machine learning algorithms to solve visual analytics problems arising from real-world applications. The majority of our ongoing research projects can be categorized into one of the following three areas – 1. Data-efficient deep learning (zero-shot/few shot learning etc.), 2. Learning across modalities/domains (e.g., text-based image retrieval, sketch-guided localization, visual question answering, domain adaptation etc.) and 3. Video surveillance (e.g., person-reidentification, anomaly detection, human gait and pose analysis etc.)

Interview topics: Linear Algebra, Probability and Machine Learning basics.

Prior training: Students must have a Bachelor’s or Master’s degree in Computer Science , Information Technology, Electrical, Electronics and/or Communications or in any other closely related areas. Strong programming skills are expected.

Recent News

  • Siemens Healthineers, along with IISc, inaugurated a collaborative laboratory for Artificial Intelligence in Precision Medicine.
  • Prof. Venkatesh Babu has been recognized as top top-cited chapter author by Springer Nature for the period 2013-2022. 
  • Dr. Chirag Jain receives India Alliance DBT-Wellcome Trust Intermediate Fellowship
  • Jogendra Nath Kundu receives 2023 IKDD Doctoral Dissertation in Data Science Runner-up award
  • CDS welcomes new Chair, Prof. Venkatesh Babu

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iisc physics phd students

Why Physics? Physics can be thought of as the science of motion. From the smallest subatomic particles to the largest, most distant galaxies, motion in nature occurs over an incredible range of length and time scales. Physics encompasses this entire domain. As such, it is regarded by many as the most basic and fundamental of the sciences, crucial for understanding the world around us, the world inside us, and the world beyond us; and the basis of many other sciences, including chemistry, oceanography, seismology, and astro-

-nomy.The ideas that Physics has generated, such as relativity, quantum physics, string theory, etc., are incredibly beautiful and captivating, and challenge our imagination. Physics underlies many great inventions of modern technology, like computers, cell phones, lasers, the internet, etc., that have changed our lives, and is indespensable for many of the future technological challenges facing us.

What does the programme offer? During the first three semesters of the 4-year Bachelor of Science (Research) Programme programme in IISc, all the students will be taught a rich mix of fundamental courses in the sciences, namely Physics, Chemistry, Mathematics, and Biology, as well as a basic foundation in the principles of Engineering. This multi-disciplinary learning will be a tremendous asset for all the students, and especially so for those who would want to pursue advanced degrees in emerging interdisciplinary areas wherein major strides are expected in the coming decades. In addition, all the students will also be exposed to several courses in humanities that will provide them with a better appreciation of science and its societal implications, as well as sharpen their skills in communicating science both to experts in their fields and to society at large. In particular, the 3 Introductory level Physics courses that are part of this palette of compulsory courses are designed to impart a clear, hands-on understanding of basic physics that will more than adequately equip the students to handle the physics issues that are likely to arise in any of the 5 major streams other than Physics. After the successful completion of the first three semesters, students majoring in Physics will be required to

take a fixed number of core-courses in Physics that will give them the requisite foundation to pursue any specialized area in Physics. Students can then acquire additional expertise in special areas of their choice by crediting elective courses from among a wide range of special topics courses that will enable them fulfil their minimum credit requirements for majoring in Physics; additional elective courses in any of the other science/engineering disciplines could lead to a minor specialization, provided the minimum credit requirements for doing so are met. The course structure is designed to impart the students with the requisite theory background in addition to providing strong hands-on laboratory training in modern, currently active, areas of Physics. An important feature of the programme is also the opportunity that the students will have to carry out a small research project during their final year, in any of a wide range of contemporary topics under the supervision of any of the Physics faculty members in the the Physical Sciences Division. This provides an ideal environment for translating class room learning to cutting-edge research applications.

What after a Bachelor of Science (Research) Programme in Physics? The programme design will ensure that graduating students majoring in Physics will have completed the standard pre-requisites for them to take up doctoral programmes in Physics as well as in many allied fields in graduate schools in India and abroad. The multidisciplinary and interdisciplinary skills they will have acquired will be of tremendous value to them especially if they choose to enter such cutting edge research areas as nano-scale physics or technology, physics of biomolecules or biomedical applications, etc., be it in Academia or in Industry. The physics components of the programme will be taught by the highly accompl-

-ished faculty of the Physics department, established in 1933 by the Nobel Laureate C.V. Raman, the Centre for High Energy Physics, and the Department of Instrumentation and Applied Physics in IISc, which have been leading centres in India for advanced postgraduate education and cutting-edge research in physics and its applications for several decades. We believe that the graduates of the programme will go on to distinguished careers in science and occupy leading positions in research institutes and industrial laboratories in India and the world over.

To know more details about the curriculum and content of the courses, click here .

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The Indiana University STEM Summer Scholars Institute (STEM SSI) is an 8-week undergraduate research program designed to give motivated undergraduate students hands-on experience in graduate-level research.

We welcome applicants from IU, IUI, and Minority Serving Institution (MSI) partner institutions around the United States who are seriously considering joining a Ph.D. graduate program after completing their undergraduate degree.

Students from underrepresented groups are strongly encouraged to apply.

Learn more about the STEM SSI Program

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The STEM SSI emphasizes direct laboratory experience. Students spend the majority of their time learning research techniques in the laboratory, attending lab meetings, interacting with members of other labs, and otherwise conducting themselves just as if they were in graduate school. Each student is mentored by a faculty mentor and solving real research problems in a research laboratory.

In addition to laboratory research, the program features:

  • Competitive stipend and included travel
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Computational Design

MSCD | PhD-CD

The Computational Design (CD) program investigates creative opportunities and critical issues at the nexus of design and computation. Fundamentally interdisciplinary, it mobilizes Carnegie Mellon University’s computational strengths critically towards design, architecture, and other creative disciplines.

Daniel Cardoso Llach

Associate Professor & CD Track Chair

Daniel Cardoso Llach

With a shared emphasis on critical technical practice, faculty and students in the program draw from fields including computer science, robotics, human-machine interaction, machine learning, art, and science and technology studies to illuminate emerging potentials as well as unforeseen consequences of new technologies in design. The program examines topics including robotically-supported construction, machine learning- and AI-based approaches to design generation and analysis, tangible interaction, shape grammars, responsive environments, digital heritage, computational urban studies, as well as historical and ethnographic investigations into design technologies and technologically-mediated design practices. The program’s research and creative works are frequently discussed, published, and exhibited in leading national and international venues. Inherently interdisciplinary, the program invites students to forge unique curricular paths, closely interacting with field-defining researchers, educators, and mentors in the program and across the university. 

The program offers Master of Science (MS) and Doctor of Philosophy (PhD) degrees, and is well suited to highly inquisitive applicants with technical, creative, and/or critical backgrounds who are motivated to challenge disciplinary boundaries; develop a unique research agenda; and explore the intersection computation and design with creativity, technical rigor, and critical depth.

Master of Science in Computational Design

The Masters of Science in Computational Design is a two-year, research-focused program that prepares students for leading industry positions and advanced studies in the broad field of Computational Design. 

Students in the program develop technical and conceptual skills to a) formulate and develop technologies that reimagine material, sociotechnical, and/or environmental relations in design; b) approach digital systems and human-machine encounters as sites for both creative exploration and critical inquiry; and c) produce a thesis that documents a substantial work of research and a novel contribution to knowledge in the field of Computational Design.

Responsive Robotic Assembly with Heterogeneous Raw Wood. Jiaying Wei, MSCD 2023

The program’s curriculum is structured around a lean sequence of research seminars that builds cohesive cohorts, explores the field’s technical, conceptual, and historical underpinnings, and introduces a variety of approaches to research in the field. Selective courses, special topics seminars, and faculty-led independent studies and research groups delve deeper into technical and critical issues, and help instigate the development of unique theses. With guidance from faculty advisors, students define a sequence of courses providing a solid technical understanding of computational concepts and techniques. The precise choice and sequence is based on each student’s prior skill level and their research orientation. In addition, a vast pool of eligible extra departmental courses gives students the opportunity to enrich their methodological and conceptual toolkits further. During the second year, students form advisory committees and develop their theses. Of publishable, or close to publishable, quality, theses in the program rigorously document the definition, prototyping, and critical interrogation of design-technological systems, and/or their histories and the communities they support. 

The program’s typical duration is four semesters. Students must complete a minimum of 147 units of coursework including a 36 unit thesis for graduation. Proficient candidates with prior relevant experience may be considered for advanced standing, subject to approval of the faculty committee upon admission based on a proposed plan of studies. In all cases, full-time registration must be maintained for the first three semesters.

MSCD Curriculum

Doctor of Philosophy in Computational Design

The Doctor of Philosophy in Computational Design prepares students for careers as leading educators, scholars, and researchers in academia and industry. The program offers students the opportunity to conduct research that explores Computational Design questions in greater technical and critical depth, resulting in novel and original contributions to knowledge in the field.

Students work closely with their advisors throughout all stages of the program. Advisors are responsible for supervising and offering guidance, including working with students in the formulation of an individual plan of studies that supports both technical and conceptual elements of the student’s chosen area of concentration. Advisory committees in the doctoral program in CD must be chaired by a CD Core Faculty member, and must include one external member. External advisors might be at a different Carnegie Mellon University department, at a different institution, or in industry. Faculty currently serving as PhD advisors in the program include Profs Joshua Bard, Daragh Byrne, Daniel Cardoso Llach, and Vernelle Noel. Prospective applicants are encouraged to familiarize themselves with the work of the program and with individual advisors’ recent and ongoing research. 

Students’ doctoral path in CD is punctuated by four milestones. The first is the presentation of a game plan that specifies the student’s area of concentration within the program and a scope of work within that area comprising both a plan of studies and research activities, as well as an advisory committee. The second milestone, usually completed after fulfilling course requirements, is a written and oral examination that gives students the opportunity to demonstrate their command over technical and conceptual aspects of their area of concentration, and their ability to formulate an original research project. The third is the public presentation of their dissertation proposal, a document detailing the dissertation’s conceptual, technical, and methodological components, arguing for its relevance to the field of Computational Design, and demonstrating its viability by documenting completed and ongoing research activities. The final milestone is the public defense of their doctoral dissertation. A doctoral dissertation in CD must be a rigorous, significant, and novel contribution to knowledge in the field. It must be grounded on a deep understanding of the state of the art in the field and their specific area of concentration, as well as a critical awareness of the broader contexts of the research.

^ A Data Informed Workflow in Design for Architecture and Urbanism. Javier Argota Sánchez-Vaquerizo, MSCD 2018

PhD-CD Curriculum

About the Program

The highly selective Computational Design graduate program at the School of Architecture at Carnegie Mellon University is a trailblazer in computational design research and pedagogy. With origins in the late 1960s, it is one of the earliest programs of its kind. Its pioneering focus on applications of computational representation and symbolic AI to design has evolved into a broader inquiry into computational modes of design interaction, materiality, and intelligence, and a sensitivity towards the cultural, material, and historical specificity of computational media in design. Today, the Computational Design program adopts a broad view of computation as a vehicle of design inquiry, as a key technical scaffolding for applied and speculative design research, and as a worthy subject of scholarly analysis and debate. 

More than mere instruments, computational methods and ideas — including those linked to recent developments in machine learning/AI, virtual and augmented reality, and robotics — configure new technical infrastructures and imaginaries. Shaping contemporary spaces, artifacts, materials, and labors, these also configure new conceptions of design and creativity. Embracing this complex context, the Computational Design program works to develop new knowledge that harnesses computational ideas and methods towards humane, ecological, and creative environments, and that reimagines the interplay of the technological, the social, and the material in design.

^ Interfacing the Multiplexer Room: Speculative Spatio-Mediated Assemblages for the Digitally Interfered Home. Policarpo Del Campo Baquera, MSCD 2021

MSCD thesis presentations and discussions at CODE Lab (photo credit: Chitika Vasudeva).

Computational Design students occupy the Computational Design Laboratory (CODe Lab) , a beautiful double-height space strategically located in the Margaret Morrison building’s fourth floor, and its two adjacent suites. Aside from workspaces and an area for presentations and collaborative work, the lab houses a fabrication space equipped with a variety of tools to support research including desktop digital and hand fabrication tools, an electronics workbench, as well as dedicated terminals for specialized data and graphics processing and virtual/augmented reality research. 

In addition, CD students have access to many other School of Architecture and Carnegie Mellon University’s world-class laboratories and facilities, including the Design Fabrication Laboratory (dFAB) and Applied Architectural Robotics Laboratory. They often participate in research and learning activities at other labs including the Frank Ratchye STUDIO for Creative Inquiry , the College of Fine Arts’ research hub, and the Manufacturing Futures Institute at Mill 19 , among others.

Extracurricular activities including yearly lecture series and workshops by leading computational design scholars and practitioners further enrich the program, fostering a vibrant atmosphere of research, learning, and creativity.

Program Faculty

Joshua Bard

Joshua Bard

Associate Professor & Associate Head for Design Research

Daragh Byrne

Daragh Byrne

Associate Teaching Professor

Dana Cupkova

Dana Cupkova

Associate Professor & MSSD Track Chair

Jeremy Ficca

Jeremy Ficca

Associate Professor, MAAD Track Chair & dFAB Lab Director

Sinan Goral

Sinan Goral

Adjunct Faculty

Matthew Huber

Matthew Huber

Special Faculty

Omar Khan

Professor & Head

Kristen Kurland

Kristen Kurland

Teaching Professor

Vernelle A. A. Noel

Vernelle A. A. Noel

Lucian and Rita Caste Assistant Professor in Architecture

Paul Pangaro

Paul Pangaro

Visiting Scholar in Computational Design

Admissions Resources

Are you a current student looking for resources? Handbooks, procedures and other information can be found on the Student Resources page .

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Hopkins Engineering online graduate master's programs again ranked among nation's best

Three whiting school of engineering online programs now occupy the no. 1 spot.

By Lisa Ercolano

Johns Hopkins Engineering's online graduate degree programs continue to be recognized by U.S. News & World Report as among the nation's best.

Multiple Engineering for Professionals (EP) programs are ranked No. 1, including its online computer information technology offerings, which share the top spot with Columbia University. Rankings in this category considered data from five EP fields: computer science, artificial intelligence, cybersecurity, information systems engineering, and data science.

Also in the No. 1 spot are EP's Engineering Management and Electrical and Computer Engineering programs, which are tied with Purdue University and Georgia Institute of Technology, respectively.

EP's online programs overall now rank No. 6 in the nation among the publication's Best Online Master's in Engineering Programs, moving up three places from last year into a tie with the University of Maryland, College Park.

Specialty rankings include:

  • Industrial/systems engineering is No. 8
  • Mechanical engineering is No. 7
  • Civil engineering is No. 7 (tied with the University of Wisconsin and UCLA)

"Our continued climb in the rankings speaks volumes about our ability to equip working professional engineers with in-demand skills and knowledge through classes offering the highest standard of educational excellence," said Dan Horn, associate vice dean for professional education and lifelong learning at the Whiting School of Engineering . "I expect our upward momentum to continue as we constantly reimagine our offerings to meet the ever-changing needs of our student population."

U.S. News' Best Online Engineering Programs includes a review of 21 online master's degree programs in the Whiting School of Engineering, including those listed above as well as the following programs: applied and computational mathematics; applied biomedical engineering; applied physics; environmental engineering, science and management; financial mathematics; healthcare systems engineering; materials science and engineering; robotics and autonomous systems; and space systems engineering. The Best Online Computer Information Technology Programs category includes a review of online and part-time programs at JHU in artificial intelligence, computer science, cybersecurity, data science, and information systems engineering.

U.S. News ranks the nation's best online graduate programs in seven disciplines, as well as the best online bachelor's degree programs. Rankings are determined by five weighted criteria: student engagement, faculty credentials and training, student services and technology, peer reputation, and admissions selectivity.

More than 6,500 students globally are enrolled in Johns Hopkins University's Whiting School of Engineering online and part-time programs. Its top-ranked courses and curricula are created by faculty members and program leadership who are experts in their field. Instructional designers support the faculty in customizing the courses for online delivery and maximum student engagement and learning.

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Tagged u.s. news and world report , engineering for professionals , university rankings

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How to Select an Online College or University

Verifying accreditation can ensure the legitimacy of an online program, experts say.

How to Select an Online College

Happy young woman using laptop sitting at desk writing notes while watching webinar, studying online, looking at pc screen learning web classes or having virtual call meeting remote working from home.

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Some online programs are synchronous, meaning there is a live component where the professor and students are logged in together, but many are not.

Whether it's to pursue an associate, bachelor's or advanced degree , online programs offer flexibility for those whose life circumstances make attending in-person college classes impractical. Some online programs are also available at a fraction of the cost of brick-and-mortar colleges .

But it takes discipline and structure to succeed in an online format, experts say. Online courses generally are delivered through a learning management system – a virtual portal that serves as a classroom – where students can access course work and materials as well as monitor their progress on lessons and grades.

Some online programs are synchronous, meaning there is a live component where the professor and students are logged in together. But many are not and have little or no live aspect.

The flexibility of online programs is often what attracts people the most, but experts say it's crucial for prospective students to consider their own personality and tendencies when evaluating whether an online program is right for them.

“These flexible online programs often attract people who fare poorly with a lack of structure and more freedom," says Allen Koh, CEO of education consulting firm Cardinal Education. "For a lot of people, I really encourage them to think about structure a little favorably, especially since education costs so much. It could help them get out more quickly."

The next step, experts say, is to conduct thorough research on a variety of programs to determine the best fit. Here's what to look for.

Accreditation

When it comes to picking any degree program, legitimacy matters. Experts say a key indicator of legitimacy is accreditation , a process where an outside authority ensures that a school or specific degree program – whether on campus, online or blended – meets certain standards of quality.

Schools must also be accredited by a "nationally recognized" accrediting agency, such as the Higher Learning Commission or the Council for Higher Education Accreditation, for students to receive federal financial aid, according to the U.S. Department of Education. It's a voluntary process, but a program that lacks accreditation is a red flag, experts say.

"Some programs operate without accreditation, focusing primarily on profit," Pierre Huguet, CEO and founder of admissions consulting firm H&C Education, wrote in an email. "A degree from a non-accredited college or university is often not valued as proof of competence by employers. Accreditation assures that the courses are rigorous and meet the standards of other institutions that grant similar degrees."

Colleges typically list their accreditation directly on their website, but prospective students can also verify accreditation of specific universities and programs through the Education Department's Office of Postsecondary Education accreditation database . The website also details whether a school is on probation or has lost accreditation, as well as their next accreditation review date.

For specific career paths, programmatic accreditations are crucial and can help immensely in landing a job, says Leah Pottle, director of online admissions for St. Joseph's College in Maine.

"Programmatic accreditation should also give prospective students extra comfort, since it serves as a secondary layer of quality assurance," she wrote in an email. "It says that it's not just the college itself that has been reviewed and approved by an external body, but the program too has been through a rigorous review process and accepted as meeting or exceeding quality standards."

Because online programs offer more flexibility for completing course work, one of the biggest misconceptions about them is that they're easier than traditional in-person courses, experts say.

"They are actually harder for many individuals because they require you to be very good at time management," Pottle says. "You must also be diligent about making time to study and do your assignments."

Accreditation at the university and program levels gives prospective students a good starting spot to determine curriculum quality, experts say. But prospective students should also take time to explore course offerings, meet with department heads and professors and talk with former students to get a sense of coursework rigor.

If students sense that a program will lack rigor and be “easy,” that may be a sign to avoid it, says Kristen Willmott, a senior private counselor and graduate school admissions director at admissions consulting firm Top Tier Admissions.

“If you’re going to go through the trouble of working on your application and paying that application fee and ultimately diving forward with an online program, you want to make sure that the one you select jives with what you’re actually hoping to accomplish," she says.

Job Placement

Another good indicator of an online program's quality is employment statistics of graduates. If the majority of graduates land jobs in their intended field, it's typically a good sign that the program is adequately preparing students and that students are getting a good return on their investment, experts say.

Prospective students can find this information on the university's website or from the admissions office. Experts also advise directly asking job-attainment questions of the schools of interest and alumni before deciding whether to apply.

If the degree is in a field that requires licensure or certification, such as nursing , education or psychology , prospective students should ensure the program meets the necessary criteria for professional practice in the state they intend to work, Huguet says.

"For instance, some schools offer general psychological education that doesn’t meet state requirements for licensure," he says. "For students who have gone through non-accredited, sub-standard programs, this could mean signing up for additional courses or paying out-of-pocket for supervised training from licensed professionals."

The price tag of an online college should be considered, including how the cost compares to attending a brick-and-mortar school. This information is generally available on the university's website. The tuition number shown may not always be the actual price, though. Experts caution prospective students to be aware of hidden fees when applying to online programs.

"Many schools will boast a lower tuition rate and then, after you commit to enroll with them, tack on a bunch of fees," Pottle says. "Fees are not necessarily a red flag , but you want to be aware of them, and a school should be happy to be transparent with you about them – what they're for, how much they are, and how they're added on. For example, are they per credit, per class or per semester?"

The low costs of some online programs can be attractive, but experts advise prospective students to be cautious. Something that seems too good to be true, such as earning a degree in a very short time or at an extremely low cost, could be a warning sign. If a program seems abnormally expensive, gather more information.

"Also, be cautious of programs that require large payments upfront," Huguet says. "Accredited programs must follow strict ethical rules regarding funding requests and offerings."

Scholarships and financial aid may be available, so prospective students should speak with the financial aid office and explore third-party scholarships. A common misconception is that there's less financial aid for online programs than in-person programs, but experts say it's mostly identical and that online students have the same access to federal financial aid and merit-based or need-based scholarships.

"Also, don't forget to check in with your employer about tuition assistance or reimbursement," Pottle says. "If your job does offer this, make sure to talk with your human resources department and your prospective school to see how you can best maximize that benefit and reduce your own out-of-pocket cost."

Student Services and Support

Online students don't have many of the advantages that in-person students have, such as access to physical spaces like computer labs and libraries or face-to-face meetings with professors and classmates. But many schools make some of these resources available digitally, such as copies of books or office hours with professors .

Part of the process of vetting a program is exploring what services and support are available for students.

"What does this school you're looking at have in place to help you reach your goals?" Pottle says. "Is tutoring available? What does that cost? Will you have an adviser that's specifically assigned to you? What kind of career support is there? These are all very valid questions to help you compare and contrast institutions and find the best college for you."

Trying to fund your online education? Get tips and more in the U.S. News  Paying for Online Education  center.

What Employers Think of Online Degrees

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2024 Best Colleges

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AI unlocks ancient text owned by Caesar's family

  • Published 4 days ago

Burnt scroll lies on white table

Three students have won a $700,000 prize after using AI to read a 2,000-year-old scroll burnt during the Mount Vesuvius eruption in 79AD.

The ancient text was unreadable until now after being charred in the Roman town of Herculaneum during the same eruption that destroyed Pompeii.

It is thought to have belonged to Julius Caesar's father-in-law and talks of music and food.

Experts have called the breakthrough a "revolution" in Greek philosophy.

Scholars believe the style of the writing is typical of the Greek philosopher Philodemus, who followed the teachings of Epicurus, and may have been philosopher-in-residence at Herculaneum.

In the 18th century hundreds of papyrus scrolls were discovered in the library of a luxurious a villa in the town - the only such library of texts from ancient Roman times to be discovered.

But their contents remained a mystery to scholars - they were so badly burnt by volcanic debris that when they attempted to unroll them they fell apart in their hands.

Dr Federica, papyrology researcher at the University of Naples, said this "curse" is also their saving grace. The high temperatures of the eruption carbonised and preserved the scripts which would have typically decomposed.

Last year a breakthrough came when Dr Brent Seales and his team at the University of Kentucky used high resolution CT scans to unroll the texts, but the black carbon ink used on the scripts was indecipherable from the papyrus itself.

Dr Seales worked with tech investors to launch the Vesuvius Challenge, a $1m (£790,000) prize for anyone that could come up with a solution.

A team of three students, not working in philosophy but tech, realised artificial intelligence may be able to provide the solution.

Inside of a villa with mosaics on wall

Youssef Nader, a PhD student in Berlin, Luke Farritor, a SpaceX intern and student, and Julian Schillinger, a Swiss Robotics student, built an AI model that was able to work out the lettering through using pattern recognition.

Dr Federica said: "This is the start of a revolution in Greek philosophy in general."

Greek letters are highlighted on the scanned scroll

The model has so far deciphered 2,000 Greek characters written in one of the four scrolls scanned by Dr Seales' team - which is only 5% of the text.

Now translated the characters reveal the author discussing the sources of pleasure in life, referencing music and food.

In one passage Philodemus questions whether things in lesser quantities bring more pleasure: "as too in the case of food, we do not right away believe things that are scarce to be absolutely more pleasant than those which are abundant."

The team behind the Vesuvius Challenge hope the technology can be used to read 90% of all four scrolls scanned this year, and eventually all 800.

Related Topics

  • Artificial intelligence
  • Ancient Rome

More on this story

Astonishing new finds in the ancient city of Pompeii

  • Published 19 July 2023

A three-dimensional serpent slivers up a burgundy background

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Nyc teacher, former prodigy took student into bathroom — before handing him wad of cash: probe.

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A former prodigy at the prestigious Bronx High School of Science who went on to become a city chemistry teacher resigned last year after she “engaged in an inappropriate relationship” with a male student in the Manhattan high school where she taught, an investigation found.

Shoshana Leffler, 37, was once a star student at the Bronx High School, where she and her twin brother Abba were both among 300 semifinalists in the nationwide Intel Science Talent Search.

She attended Princeton and NYU, then landed a teaching job in 2019 with the city Department of Education.

But in February 2023, Leffler, then 36, was caught on video taking a 17-year-old male student into a locked bathroom at the High School for Health Careers and Sciences in Manhattan’s Fort George — then later handing the teen a wad of cash.

Stas Shvartsman, professor of chemical engineering and genomics (left), and Shoshana Leffler, a chemistry major working with scientific equipment.

“What occurred in the bathroom can only be speculated about since Leffler resigned from the DOE without providing an explanation,” Anastasia Coleman, the Special Commissioner of Investigation for city schools, said in a report obtained by The Post.

A surveillance camera in the school’s stairwell first picked up Leffler and the unnamed student “engaging in conversation” at 10:35 am on a Tuesday morning — one minute into the fourth period, when the teen “should have been in class,” the SCI report says.

An assistant principal spotted the two and rebuked Leffler for the improper tete-a-tete.

But instead of ending the encounter, she took the boy to the building’s fifth floor, the report states.

The High School for Health Careers and Sciences building with a tower and trees.

There, they “sought out a private room where security cameras could not record them,” investigators concluded — a staff bathroom with a lockable door.

Their seven-minute lavatory rendezvous ended when another faculty member arrived to use the facilities and found the bathroom locked from the inside.

Once the interrupting staffer departed, Leffler and the teen were filmed leaving separately.

The next day, Leffler met up with the student in the stairwell again, where she was recorded “handing [him] what appeared to be money, him pocketing this money, and them leaving the stairwell together,” the report says.

Investigators found no evidence of contact between Leffler and the boy in the teacher’s phone records.

The student would not testify about the incident.

Leffler quit while the probe was ongoing, and later refused to be questioned, leaving the nature of their relationship a mystery.

A “problem code” was attached to Leffler’s DOE file, which could bar her from future employment with the city.

The SCI forwarded its report to the New York State Department of Education for possible action, but she remains licensed to teach in New York, records show. 

Shoshana earned a Ph.D. in medical science from NYU with a dissertation on brain-cell development .

Abba is now a top pharma researcher with a string of patents and peer-reviewed papers to his credit — and both twins still live with their parents in the northern Bronx, according to public records.

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“These are the students who, God willing, will find cures for diseases and will be our political leaders,” then-Bronx Science Principal Valerie Reidy told The Post in 2005.

Neither Leffler nor her attorney responded to requests for comment.

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  2. Department of Physics

    The largest number of Ph.D.s in physics in India -- 110 since 1998 -- come from this department. Graduates from the department have gone on to distinguished careers in science and occupy leading positions in research institutes in India and the world over. ...more Research Highlights

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    Meet the students of the Department of Physics at IISc, the premier institute for advanced scientific and technological research and education in India. Learn about their academic backgrounds, research interests, and achievements in various fields of physics, from astronomy and astrophysics to condensed matter and quantum devices.

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    Integrated Ph. D. Programmes The Institute offers exciting opportunities to motivated and talented Bachelor's degree holders with a keen sense of scientific enquiry for pursuing advanced research in frontier areas of Biological, Chemical, Physical and Mathematical Sciences leading to a Ph D degree.

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    Physics (PH) Solid State and Structural Chemistry (SS) Ph.D. Engineering/M.Tech. (Research) Students with a B.E./B.Tech. degree and a GATE score who meet the basic qualification for eligibility for the relevant engineering departments are eligible to be considered both for the Ph.D. program as well as the M.Tech. (Research) program.

  6. Department of Physics

    Professor Spintronics, magnetic nano-structures, surface and thin film magnetism, magneto- transport in metallic multilayers and oxides, spin-polarized electron scattering. Phone: 080-2293 2632 User ID: anil AT iisc.ac.in Web: http://www.physics.iisc.ac.in/~anil

  7. Admissions

    The IPC department accepts students into two PhD programmes, viz. regular and integrated PhD programmes. The Regular PhD programme is a post-Master's degree programme, and has a typical duration of 5 years. Once the admitted students join a research group, they begin their work under the guidance of their research advisor.

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    History. The Department of Physics was established in the year 1933 by Prof. Sir C.V. Raman. It soon evolved into an advanced centre for research with outstanding work in optics and spectroscopy. Several illustrious names of Indian Science such as Homi Bhabha, Vikram Sarabhai, R.S.Krishnan, G.N.Ramachandran and S.Ramaseshan have been associated ...

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    Integrated PhD Programme in Physical Sciences. Joint Astronomy Programme (students wishing to apply for this Programme should indicate Astronomy and Astrophysics as one of their department preferences when filling up the application form for Research Programmes). For information on how to apply for these Programmes in IISc, click here.

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    The IISc astrophysics group started in 1986. We also coordinate the Joint Astronomy Programme (JAP) - a programme for training PhD students in astrophysics, jointly run with several collaborating institutes within Bangalore: Raman Research Institute (RRI) Indian Institute of Astrophysics (IIA) Indian Space Research Organisation (ISRO)

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    M.Tech II year Students Phd MSc MTech. SL No. Name: S.R. NO 1. Manjunath Hegde: 06-02-01-10-51-14-1-11054 ... Siemens Healthineers, along with IISc, inaugurated a collaborative laboratory for Artificial Intelligence in Precision Medicine. ... Indian Institute of Science Bangalore, India 560012 Phone: +91-80-2293 2789.

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    00:00. 00:49. A former prodigy at the prestigious Bronx High School of Science who went on to become a city chemistry teacher resigned last year after she "engaged in an inappropriate ...