Junior Research Fellow (JRF) Recruitment 2026 at NIT Kurukshetra and IIT Indore – ANRF PAIR SAKSHAM Project

Junior Research Fellow (JRF) Recruitment 2026 at NIT Kurukshetra and IIT Indore – ANRF PAIR SAKSHAM Project

National Institute of Technology Kurukshetra (NIT Kurukshetra), in collaboration with Indian Institute of Technology Indore (IIT Indore), invites applications for 02 Junior Research Fellow (JRF) positions under the ANRF-funded research project “SAKSHAM – Scientific Advancements in Knowledge for Sustainability, Healthcare, and Materials.”

The positions are associated with research in Health and Medical Technologies (HMT), focusing on Artificial Intelligence, Deep Learning, Antimicrobial Resistance Diagnostics, and Drug Discovery.

Position Overview

About the Opportunity

Applications are invited from motivated and eligible candidates for two JRF positions under the ANRF PAIR SAKSHAM research project.

The research focuses on developing AI-based diagnostic and predictive solutions for antimicrobial resistance and healthcare applications.

The project will be implemented at NIT Kurukshetra (Spoke Institution) in collaboration with IIT Indore (Hub Institution).

The workplace may vary depending on project requirements at the Spoke and Hub institutions.

Available Research Positions

1. Junior Research Fellow (JRF) – Deep Learning for Antimicrobial Resistance Diagnostics

Research Focus

The project involves developing a genetic algorithm-based framework for testing the robustness of deep learning models used in antimicrobial resistance diagnostics and therapeutics.

2. Junior Research Fellow (JRF) – Machine Learning for Antimicrobial Resistance Prediction

Research Focus

The project focuses on developing interpretable and efficient machine learning models to predict antimicrobial resistance to drugs.

Essential Qualifications

Candidates must meet one of the following educational requirements.

Option 1: Postgraduate Engineering/Technology Qualification

• Postgraduate degree in Engineering/Technology with at least 60% aggregate marks or 6.5 CGPA on a 10-point scale.

• Candidates must have qualified GATE.

GATE Exemption: The GATE requirement is waived for candidates with a CGPA of 8.0/10.0 in the qualifying degree from a UGC-recognized university, institute, or autonomous body, as stated in the advertisement.

Final-Year Postgraduate Students

Applicants in the final year of their Master's programme who have submitted their dissertation or thesis but have not received their final-semester results may apply.

However, they must submit their results by 30 November 2026. Otherwise, any JRF offer made to them will be cancelled.

OR

Option 2: Undergraduate Engineering/Technology Qualification

• Full-time Bachelor's degree in Engineering/Technology or equivalent.

• Minimum 75% aggregate marks or 8.0 CGPA on a 10-point scale.

Research Areas

The advertised projects are associated with:

• Artificial Intelligence and Machine Learning

• Deep Learning

• Genetic Algorithms

• Antimicrobial Resistance Diagnostics

• Interpretable Machine Learning

• Healthcare and Medical Technologies

• AI-Based Drug Resistance Prediction

• Computational Healthcare Research

Appointment Duration

The exact appointment duration and extension conditions are not visible in the provided excerpt.

The positions are associated with the ANRF PAIR SAKSHAM research project.

Selection Process

The selection process, interview schedule, and shortlisting procedure are not specified in the visible portion of the advertisement.

Applicants should refer to the complete recruitment notification for further instructions.

How to Apply

Interested and eligible candidates should refer to the official recruitment announcements of NIT Kurukshetra for the application procedure, required documents, and submission instructions.

Official Institute Website: https://nitkkr.ac.in/

Collaborating Institute Website: https://www.iiti.ac.in/

The specific application form or submission link is not visible in the provided excerpt.

Important Dates

Job Domain (for classification): Computer Science & Engineering – Artificial Intelligence, Machine Learning, Deep Learning, Healthcare Technology, and Computational Drug Discovery.

Note: The uploaded image contains only part of the recruitment advertisement. Fellowship details, application deadline, application procedure, and appointment duration should be confirmed from the complete official notification before publication.

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