VacancyBook

IISER Bhopal JRF and Project Associate-I Recruitment 2026

Posted 12 Oct 2026Updated 12 Oct 2026CRG/2023/000970
Total Vacancies
—
Last Date
14 Oct
Closed
Apply Mode
Email
Contract
Status
Application Closed
Recruitment status
Applications closed on 14 Oct 2026
  1. Notification29 Sept
  2. Applications Open
  3. Applications Closed14 Oct

About IISER Bhopal JRF and Project Associate-I Recruitment 2026

IISER Bhopal, a premier research and teaching institute in Madhya Pradesh, has invited applications for the post of Junior Research Fellow or Project Associate-I under an ANRF-funded project in theoretical and computational biological physics. The position sits in the Department of Chemistry and involves physics-based modelling and simulation of biomolecular systems, with a possible route to an institute-funded PhD.

Job Overview

Organization
Indian Institute of Science Education and Research Bhopal
Advertisement No.
CRG/2023/000970
Post Name
Junior Research Fellow (JRF) and Project Associate-I
Job Location
Bhopal, Madhya Pradesh
Who Can Apply
Candidates from anywhere in India
Job Type
Contract
Gender
All
Nationality
Indian
Credentials Required
Valid score/rank in NET/GATE/JEST or an equivalent national eligibility test for the JRF post; students of IISERs, IITs, NITs and IISc with a CPI above 8.0/10.0 are exempt
Tenure
6 months, or until completion of the project, subject to satisfactory performance

Vacancy Breakdown

Junior Research Fellow (JRF)
Project Associate-I
Total0

Eligibility Details

Requirements differ by post — open a post to see its own.

Junior Research Fellow (JRF)
Qualification
M.Sc. / MS / BS-MS / BS / BTech or equivalent in Physics, Engineering Sciences, Applied Mathematics, Biophysics, or Physical Chemistry from a recognised university/institute, with a minimum of 60% aggregate or a CGPA/CPI of 7.0 on a 10-point scale; valid score/rank in NET/GATE/JEST or an equivalent national eligibility test, with exemption for students of IISERs, IITs, NITs and IISc holding a CPI above 8.0/10.0
Desirable
Proficiency in computer programming (Python or any other programming/scripting language)
Project Associate-I
Qualification
M.Sc. / MS / BS-MS / BS / BTech or equivalent in Physics, Engineering Sciences, Applied Mathematics, Biophysics, or Physical Chemistry from a recognised university/institute, with a minimum of 60% aggregate or a CGPA/CPI of 7.0 on a 10-point scale, without NET/GATE/JEST qualification
Desirable
Proficiency in computer programming (Python or any other programming/scripting language)

Selection Process

  1. 1
    Shortlisting

    Applications are shortlisted from the documents submitted by email.

  2. 2
    Online Interview

    Held through Zoom or Google Meet for shortlisted candidates only; no interim correspondence is entertained.

Salary Structure

Junior Research Fellow (JRF)
Pay: INR 37,000 + HRA per month
Project Associate-I
Pay: INR 30,000 + HRA per month

How to Apply

  1. 1Prepare a cover letter, a detailed CV, names and email addresses of two referees, copies of all academic credentials including mark sheets from 10+2 onwards, and proof of NET/GATE/JEST or equivalent qualification where applicable
  2. 2Combine all the documents into a single PDF file
  3. 3Email the single PDF to [email protected] on or before 14 October 2026

Documents to Carry / Upload

•Cover letter
•Detailed CV
•Names and email addresses of two referees
•Copies of all academic credentials including mark sheets from 10+2 onwards
•Proof of NET/GATE/JEST or equivalent qualification where applicable

Important Details

  • The project position may be converted into an institute-funded PhD in the near future.
  • Only shortlisted applicants will be contacted by email for the online interview, and no interim correspondence will be entertained.

Project Description

The project lies at the interface of physics, biology and computation. Using physics-based models and simulations, it explores the fundamental physical principles governing complex biomolecular systems, with particular emphasis on phenomena spanning multiple time and length scales. The work employs advanced computational methods rooted in equilibrium and non-equilibrium statistical physics, along with modern machine learning techniques.

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