Post-Doctoral Programme at Vachani School of Advanced Computing - Ashoka University

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Post-Doctoral Programme at Vachani School of Advanced Computing

The Vachani School of Advanced Computing at Ashoka University invites applications from exceptionally qualified and accomplished researchers for appointment to the position of Post-Doctoral Fellow (full-time).

This programme has been instituted with the objective of advancing research in the broad areas of Computer Science, Data Science, Artificial Intelligence, and interdisciplinary convergences, while consolidating the academic research environment of the University, enhancing scholarly output, and nurturing researchers of distinction who may contribute to the academic and scientific community at the highest levels.

The Vachani School of Advanced Computing (VSAC) is focused on creating a unique academic and research ecosystem in frontier areas of Computer Science, Data Science, Artificial Intelligence, and exploring novel synergies across different domains, leading to new forms of knowledge, creativity, and problem-solving.

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Eligibility

Academic Qualifications

  • A doctoral degree (PhD) in Computer Science/Data Science/Artificial Intelligence/Mathematics/Statistics or other domains, with adequate evidence of research in the areas of Computer Science, Artificial Intelligence, and Data Science, from a recognised university or research institution of repute.
  • Those who have submitted their PhD thesis and are awaiting the award of the degree are also eligible to apply. However, such candidates, if selected, will be offered a lower fellowship amount until they qualify for the eligible degree. The degree must be submitted within one year from the date of joining to continue.

Age Limit

  • The upper age limit is 40 years.

Required documents to complete the application process

  • CV of the applicant, providing academic trajectory, published papers, and the names of three referees
  • Copy of PhD and Master’s degree certificates and any other relevant documents (previous work experience certificate, if any)
  • A proposal containing a brief (two pages or fewer), single-spaced description of the proposed research project, including background, key objectives, and significance
  • Two letters of recommendation from among the referees listed

Recruitment Process

  • In-person or online interview. 

Remuneration and Benefits

  • Fellowship – INR 1,00,000 per month + 9% HRA
  • Research grant – INR 2,00,000 per annum
  • Insurance – Medical insurance of INR 1,50,000

Duties and Responsibilities

  1. Undertake original, rigorous, and high-quality research in frontier areas within the School’s designated thrust domains, in active collaboration with the assigned faculty research groups
  2. Disseminate research findings through publications in peer-reviewed scientific journals of international repute, and present scholarly work at recognised national and international conferences, with due acknowledgement of Ashoka University affiliation
  3. Assist in academic instruction by conducting laboratory sessions, delivering tutorials, and supporting course-related activities as assigned by the School
  4. Post-Doctoral Fellows shall be affiliated to a research group rather than to a single faculty member, with a view to fostering collaborative, cross-disciplinary scholarly engagement

Tenure of Appointment

Initial contract of one year, extendable up to two years at the discretion of the Dean, Vachani School of Advanced Computing.

Research Areas (indicative & non-exhaustive)

Fellows appointed under this programme shall be expected to make substantive contributions to one or more of the following indicative thrust areas, in active collaboration with members of the School’s faculty. The enumeration below is indicative in nature and is not to be construed as exhaustive.

  • Algorithms
  • Programming Languages
  • Learning Technologies
  • Cryptography
  • Formal Methods and Automated Reasoning
  • Software Engineering
  • Data Science (DS)
  • Digital Health
  • Digital Heritage
  • Computer Vision
  • Natural Language Processing
  • Multimodal Reasoning
  • Bio-AI
  • Social Networks
  • Physical AI
  • AR-VR
  • Neuro-AI
  • Digitalisation, AI and Society
  • Quantum Computing

Faculty Profiles

Fellows appointed under this programme shall pursue their research in close association with one or more of the following distinguished faculty members at the Vachani School of Advanced Computing and the Department of Computer Science, Ashoka University:

Faculty Member Designation Research Areas Credentials
Santanu Chaudhury Professor and Dean, Vachani School of Advanced Computing Computer Vision, Artificial Intelligence, AI Applications, Digital Heritage, AR/VR and multi-sensory media PhD, IIT Kharagpur
Subhashis Banerjee Professor and Head, Department of Computer Science Digitalisation and Society: Computer Vision PhD, IISc Bangalore
Partha Pratim Das Professor Image Processing; Digital Geometry; Software Engineering PhD, IIT Kharagpur
Lipika Dey Professor Natural Language Processing; Artificial Intelligence; Data Science PhD, IIT Kharagpur
Debayan Gupta Assistant Professor Cryptography; Secure Multi-Party Computation; Privacy; Databases PhD, Yale University
Mahavir Jhawar Associate Professor Cryptography; Network Security PhD, ISI Kolkata
Sandeep Juneja Professor Applied Probability; Sequential Learning; Simulation Theory; Computational Finance; Games in Queues PhD, Stanford University
Rintu Kutum Faculty Fellow Augmented Intelligence; Genomics; Digital Health PhD, CSIR-Institute of Genomics and Integrative Biology
Dheeraj Sanghi Professor Computer Networks PhD, University of Maryland
Sandeep Sen Professor Algorithms and Complexity PhD, Duke University
Raghavendra Singh Visiting Professor Computer Vision PhD, University of Southern California
Anirban Sen Assistant Professor Computational Social Science; Social Media/Network Analysis and Mining PhD, IIT Delhi
Aalok Thakkar Assistant Professor Formal Logic and Artificial Intelligence PhD, University of Pennsylvania
Ashesh Assistant Professor Computer Vision PhD, TU Dresden

 

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