BITS Pilani JRF Computer Science Recruitment 2026

BITS Pilani JRF Computer Science Recruitment 2026: Overview

Birla Institute of Technology and Science Pilani (BITS Pilani) is hiring a Junior Research Fellow (JRF) for a contractual research project at its Pilani campus in Rajasthan. The work sits in the Department of Computer Science and Information Systems under Prof. Ashutosh Bhatia, with funding from the Defence Research and Development Organization (DRDO). The project studies encrypted network traffic using visual representations and machine learning, bringing computer science research into a focused traffic-classification problem.

Service Conditions and Caveats

• Project setting: The study combines FlowPic representations, data augmentation and contrastive learning to classify encrypted traffic. These are parts of the same project, so your research would sit within this shared theme.
• Contract basis: The notice describes the appointment as purely contractual. If you are considering the role, keep this project-based engagement in mind when deciding whether it fits your plans.
• Project tenure: The stated project duration is 1.5 years. Read this as the project's tenure; the notice does not set out a separate renewal schedule for the fellowship.
• Research environment: This is a full-time, on-campus research position at Pilani. The department and named principal investigator identify the team associated with this particular opening.
• PhD registration: Selection may allow you to register for the BITS Pilani PhD programme. You must still meet the institute's PhD qualification process and rules; the fellowship does not itself guarantee admission.

Application Submission Notes

Send your application by email to ashutosh.bhatia@pilani.bits-pilani.ac.in, the address given in the project notice. Use the subject Application for JRF -DRDO Project so your message identifies the advertised fellowship.

The notice uses an email application route; its reference to keeping material ready for a form does not include a separate form link. Address your application to the project contact above and follow the notification's stated submission instructions.

• Develop encrypted-traffic classifiers using FlowPic-style images and deep learning.
• Collect datasets and preprocess packet-capture files for research use.
• Generate time-series and FlowPic representations of network traffic.
• Implement CNN, SimCLR, CNN-LSTM-Attention and hybrid classification models.
• Evaluate models and compare their results with existing traffic-classification methods.
• Support explainability experiments using visual traffic representations.