BITS Pilani JRF Project Associate Spray Cooling 2026

BITS Pilani JRF Project Associate Recruitment 2026: Overview

Birla Institute of Technology and Science, Pilani (BITS Pilani) is recruiting a Junior Research Fellow or Project Associate-I for an Anusandhan National Research Foundation (ANRF) project in Mechanical Engineering. The contractual assignment focuses on spray cooling on engineered surfaces for high-heat-flux applications, combining experimental characterisation with machine-learning-enhanced computational fluid dynamics (CFD) modelling.

The project brings together Prof. Vadiraj Hemadri from the K. K. Birla Goa Campus as principal investigator and Prof. Aneesh A. M. from the Pilani Campus as co-principal investigator. The recruitment is listed by the Pilani Campus as full-time, on-campus research.

Service Conditions and Caveats

• Engagement: This is a contractual research position tied to the ANRF-funded spray-cooling project. The notice uses JRF and Project Associate-I as alternative designations for the same opening.
• Project period: The notice describes an initial period of two years, followed by a third year as Senior Research Fellow (SRF) after evaluation. The overall project tenure is three years, and progression to SRF depends on that evaluation.
• Doctoral registration: You may be allowed to register for the BITS Pilani PhD programme. Registration depends on meeting the institute's PhD qualification requirements; taking up the project position does not itself complete that process.

Application Submission Notes

Send your application by email to aneesh.am@pilani.bits-pilani.ac.in, the address named in the notice. This is the contact for the project application under Prof. Aneesh A. M. at the Pilani Campus.

The notice describes email submission for this opening. Use that route to send your application for the spray-cooling project; the linked career page provides the specific research notice and its supporting details.

• Develop computational fluid dynamics models for the spray-cooling project.
• Use machine learning techniques within the CFD modelling work.
• Fabricate micro-scale and nano-scale patterns on metal substrates.
• Fabricate micro-scale and nano-scale patterns on silicon substrates.
• Characterise the engineered surfaces used in the research.