JRF in Computer Vision and Deep Learning for Aerial Object Detection with PhD opportunity at NIT Rourkela National Institute of Technology Rourkela in

PRISM at the National Institute of Technology Rourkela is inviting applications for a Junior Research Fellow (JRF) position in the Department of Electronics and Communication Engineering. The project is titled Geometry-Guided Scale-Aware Framework for Object Detection in Aerial Images under Complex Conditions using Oriented Bounding Box via Gaussian-Conic Prior, with a strong focus on computer vision, deep learning, machine learning, image processing, artificial intelligence, and remote sensing.

The research group, PRISM (Perception and Recognition via Imaging and Sensing using Modern-AI), works on restoration, perception, and recognition for machine vision, with applications in unmanned autonomous systems, robotics, and intelligent monitoring/surveillance. The selected JRF will work on developing deep learning-based object detection frameworks for aerial images, evaluating performance, deploying the framework on suitable hardware, and preparing reports and research outputs.

This is a funded research position supported by the Anusandhan National Research Foundation (ANRF). The fellowship is ₹37,000/month for the first two years and ₹42,000/month in the third year, for a total project duration of 3 years. The selected candidate will also be eligible for PhD enrollment at NIT Rourkela as per institute norms.

Eligibility highlights from the official notification include a relevant M.Tech./M.E./M.S./M.Sc. Engg. degree with GATE/NET qualification in Electronics and Communication, Electrical and Electronics, Electrical, Instrumentation, Computer Science and Engineering, Computer Science, or related fields, along with minimum academic performance requirements. Strong Python programming skills and experience with PyTorch/TensorFlow are desirable. Applicants with a background in aerial scene analysis, object detection, and AI for complex environmental conditions are especially encouraged to apply.

The application deadline is 20 June 2026. Interested candidates should follow the official notification and submit the completed application with required documents as instructed. Shortlisted candidates will be contacted for an online interview.