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IIT Patna • India

Junior Research Fellow Recruitment 2026 at IIT Patna – Deep Learning & Intrusion Detection

HIRING FOR
SALARY

INR 37,000 - INR 42,000/- per month

POSTED ON
25/09/2026
LAST DATECLOSED
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ABOUT THIS POSITION

Junior Research Fellow Recruitment 2026 at IIT Patna – Deep Learning & Intrusion Detection

Indian Institute of Technology Patna (IIT Patna) invites applications for two Junior Research Fellow (JRF) positions under a time-bound research project sponsored by the Naval Research Board, DRDO. The project is based in the Department of Electrical Engineering and focuses on deep learning-based intrusion detection and classification.


Position Overview

Particulars

Details

Institution

Indian Institute of Technology Patna (IIT Patna)

Department

Electrical Engineering

Position

Junior Research Fellow (JRF)

Number of Posts

02

Advertisement No.

R&D/1086/DLD/628

Project No.

R&D/SP/EE/DLD/2024-25/1086

Project Title

Deep Learned Detection and Classification of Multiple Intrusions Using WDM Intensity and Phase-Sensitive OTDR in Underwater Environment – Phase II

Sponsoring Agency

Naval Research Board, DRDO

Appointment Type

Time-bound Research Project

Initial Duration

1 year; extendable up to a maximum of 2 years or until project completion, whichever is earlier

Location

IIT Patna, Bihta, Patna, Bihar

Application Deadline

04 October 2026

Online Interview

05 October 2026 at 2:00 PM


About the Project

The selected JRFs will contribute to a DRDO-sponsored research project involving deep learning-based detection and classification of multiple intrusions using WDM intensity and phase-sensitive OTDR technology in an underwater environment.

Candidates interested in digital signal processing, machine/deep learning and artificial intelligence are particularly encouraged.


Essential Qualification

Candidates should possess a BE/BTech/MSc/ME/MTech or equivalent degree in:

  • Electrical Engineering

  • Electronics and Communication Engineering

  • Instrumentation

  • Physics

  • Related disciplines

OR

Candidates may have a BE/BTech/MSc/ME/MTech/MCA or equivalent degree in CSE/IT or a related discipline.

Candidates must satisfy one of the following:

  • BE/BTech/MSc/MCA or equivalent with a valid GATE score (not before 2024) and minimum CPI 7.5/10 or 60% marks.

  • GATE requirement may be waived for candidates with a Bachelor's degree in Engineering from Centrally Funded Technical Institutions (CFTIs) with CGPA 8.0/10 or above.

  • ME/MTech or equivalent degree with GATE qualification (not before 2024) and minimum CPI 6.5/10 or 60% marks.


Preferred Skills

Preference will be given to candidates with knowledge or interest in:

  • Digital Signal Processing

  • Machine Learning

  • Deep Learning

  • Artificial Intelligence

GATE/NET qualification will be advantageous, although not mandatory, as stated in the advertisement.


Fellowship

  • 1st Year: INR 37,000 per month

  • 2nd Year: INR 42,000 per month


Appointment Duration

The initial appointment will be for 1 year.

It may be extended for a maximum of 2 years or until completion of the project, whichever is earlier.


Additional Opportunity

The selected candidate may be allowed to apply for the Ph.D. programme in the Electrical Engineering and Computer Science & Engineering departments at IIT Patna, subject to the institute's prescribed procedure.


Selection Process

Shortlisted candidates will be informed about the online interview.

Online Interview Date: 05 October 2026
Time: 2:00 PM

Incomplete applications will not be considered.


How to Apply

Interested and eligible candidates should fill out the prescribed application form and send the complete application form to:

Dr. Sumaneta Gupta
Department of Electrical Engineering
IIT Patna

Email: sumaneta@iitp.ac.in

Last Date to Apply: 04 October 2026

The online interview link/intimation will be sent to shortlisted candidates.


Job Domain: Engineering and Technology – Electrical Engineering / Electronics & Communication / Computer Science / Artificial Intelligence / Machine Learning / Signal Processing

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