NIT Kurukshetra Recruitment 2026 – Junior Research Fellow (JRF) Vacancies under ANRF PAIR SAKSHAM Project
NIT Kurukshetra Recruitment 2026: Apply for 2 Junior Research Fellow vacancies under the ANRF PAIR SAKSHAM project with IIT Indore. Check eligibility and apply by 20 October 2026.
Date Posted: 13 October 2026
Organization: National Institute of Technology Kurukshetra (NIT Kurukshetra)
The National Institute of Technology Kurukshetra invites applications for two Junior Research Fellow (JRF) positions under the ANRF-funded PAIR SAKSHAM research project. The project focuses on artificial intelligence, deep learning, antimicrobial resistance diagnostics, and machine learning-based drug resistance prediction, in collaboration with IIT Indore.
NIT Kurukshetra JRF Recruitment 2026 – Vacancy Details
| Particulars | Details |
|---|---|
| Organization | NIT Kurukshetra |
| Collaborating Institute | IIT Indore |
| Department | Computer Engineering |
| Post Name | Junior Research Fellow (JRF) |
| Total Vacancies | 02 |
| Advertisement Number | 31/2026 |
| Funding Agency | Anusandhan Research Foundation (ANRF) |
| Funding Programme | ANRF PAIR Program |
| Project Name | SAKSHAM – Scientific Advancements in Knowledge for Sustainability, Healthcare, and Materials |
| Research Area | Health and Medical Technologies |
| Salary | As per applicable norms |
| Job Location | NIT Kurukshetra, Haryana, with collaboration involving IIT Indore, Madhya Pradesh |
| Last Date to Apply | 20 October 2026 |
About the Research Project
The ANRF PAIR SAKSHAM project aims to advance research in healthcare and medical technologies using artificial intelligence and machine learning. The advertised positions focus on developing reliable deep learning models for antimicrobial resistance diagnostics and interpretable machine learning systems for predicting drug resistance.
The project will be implemented at NIT Kurukshetra, the Spoke Institution, in collaboration with IIT Indore, the Hub Institution.
Available Positions
1. Junior Research Fellow – Deep Learning for Antimicrobial Resistance Diagnostics
Number of Vacancies: 01
Project Title: Deep-Test-AI: A Genetic Algorithm-Based Framework for Robust Testing of Deep Learning Models in Antimicrobial Resistance Diagnostics and Therapeutics.
Lead Co-PI: Dr. Vikram Singh
Research Focus:
The project involves developing a genetic algorithm-based framework to evaluate the robustness of deep learning models used in antimicrobial resistance diagnostics and therapeutics.
2. Junior Research Fellow – Machine Learning for Antimicrobial Resistance Prediction
Number of Vacancies: 01
Project Title: Developing an Interpretable and Efficient Machine Learning Framework to Predict Antimicrobial Resistance towards Drugs.
Lead Co-PI: Dr. Yogita
Research Focus:
The project focuses on developing interpretable and efficient machine learning models to predict antimicrobial resistance to drugs, supporting research in healthcare and computational diagnostics.
Essential Qualifications
Candidates must satisfy one of the following qualification pathways, subject to the complete official notification.
Option 1: Postgraduate Engineering/Technology Qualification
- A postgraduate degree in Engineering or Technology.
- Minimum 60% aggregate marks or 6.5 CGPA on a 10-point scale.
- A valid GATE qualification is required.
GATE Exemption: As stated in the supplied advertisement, 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.
Final-Year Postgraduate Candidates:
Candidates in the final year of their Master’s programme who have submitted their dissertation or thesis but are awaiting final-semester results may apply. They must submit their results by 30 November 2026; otherwise, an offer made to them will be cancelled.
OR
Option 2: Undergraduate Engineering/Technology Qualification
- A full-time Bachelor’s degree in Engineering/Technology or an equivalent qualification.
- Minimum 75% aggregate marks or 8.0 CGPA on a 10-point scale.
Candidates should verify all applicable eligibility conditions, including any additional requirements specified in the complete notification.
Research Areas
- Artificial Intelligence and Machine Learning.
- Deep Learning and Genetic Algorithms.
- Antimicrobial Resistance Diagnostics.
- Interpretable Machine Learning.
- Healthcare and Medical Technologies.
- AI-Based Drug Resistance Prediction.
- Computational Healthcare Research.
Salary and Fellowship
The fellowship amount is listed as per applicable institute and project norms in the supplied advertisement. Candidates should consult the complete notification for the exact monthly fellowship, HRA eligibility, and other applicable benefits.
Appointment Duration
The appointment duration and extension conditions have not been specified in the supplied advertisement excerpt. The positions are associated with the ANRF PAIR SAKSHAM research project.
Selection Process
The detailed selection procedure, shortlisting criteria, and interview schedule are not specified in the supplied advertisement excerpt. Candidates should refer to the complete official notification for further information.
How to Apply
Interested and eligible candidates should follow these steps:
- Visit the official NIT Kurukshetra website.
- Locate Advertisement No. 31/2026 for the ANRF PAIR SAKSHAM project.
- Read the complete recruitment notification and confirm eligibility for the relevant JRF position.
- Check the application method, required documents, and submission instructions.
- Submit the application through the prescribed channel before the deadline.
Official Institute Website: https://nitkkr.ac.in/
Collaborating Institute Website: https://www.iiti.ac.in/
The specific application form or submission link was not included in the supplied advertisement excerpt.
Important Dates
| Event | Date |
|---|---|
| Advertisement Number | 31/2026 |
| Last Date to Apply | 20 October 2026 |
| Final-Year Master’s Students’ Result Deadline | 30 November 2026 |
| Interview Date | Not specified |
Job Location / Address:
National Institute of Technology
Kurukshetra,
Kurukshetra, Haryana,
India, with research collaboration involving
IIT Indore,
Madhya Pradesh.