Funded PhD positions open at RIVER Lab for the January 2027 session
We are looking for new PhD students for the January 2027 session. Three funded positions are available. The positions come with a stipend of Rs 37,000 per month in the first year and Rs 42,000 per month thereafter, along with campus housing.
If you join us, you will look into how human decisions shape rivers. Information on dam operations is rarely shared, and downstream communities often learn of upstream releases only after the fact. Using satellites, open software and modern machine learning, the scholars will look into ways to observe this human hand in the water cycle, model it, and make that knowledge openly available.
Research topics
- Multi-Satellite Surface Water Probe. No single satellite sees surface water well by itself. Each mission is limited by accuracy, coverage, resolution or weather. The scholar will combine existing missions, including SWOT, Sentinel, Landsat, ICESat-2, Jason-3 and SARAL-AltiKa, into one multi-sensor method for estimating water surface elevation, area and volume. SWOT, which measures both water level and extent in all weather, will anchor the calibration of the other satellites into a single, higher-frequency observing system. Modern Artificial Intelligence (AI) models will be investigated for efficacy in upsampling sparse satellite data. The ideal candidate would have prior experience in building generative AI models. Public-facing dashboards will follow in later stages. This position is on an IITB-funded project.
- Streamflow Estimation in Regulated Rivers within a Data Assimilation Framework. Dams are now central to how rivers behave, but physical hydrological models often leave out reservoir operations or treat them crudely. Building on our ResORR model, which infers river regulation from satellite estimates of reservoir operations, the scholar will fuse multi-satellite observations of water storage into basin-scale models. The aims are more accurate regulated streamflow, quantified uncertainty and decision-ready estimates. This work will explore computational modeling and statistical modeling using Machine Learning and Artificial Intelligence. This is an IITB TA position.
- Incorporating Human Agency into Data-Driven Streamflow Estimation for Regulated Rivers. Deep learning has greatly improved streamflow prediction, but it still struggles in heavily regulated basins. Our recent experiments with LSTM models point the same way: models trained on unregulated stations do best at predicting natural flow, while regulated flow demands explicit treatment of reservoir operations. The scholar will develop new machine learning approaches, or improve existing ones, that bring this human decision-making into streamflow estimation. This is an IITB TA position.
All three topics call for a demonstrable background in statistics, machine learning, data science, artificial intelligence and programming.
Who should apply
We are looking for highly motivated candidates with a background in computer science, applied mathematics, machine learning, statistics, data science, civil engineering, earth sciences or allied fields. Demonstrated technical ability in any two of programming, machine learning, statistics or data science, remote sensing, and scientific writing is desired. The rest can be picked up. A hydrology background is not required, and international applicants are welcome.
How to apply
PhD positions are filled through the formal IIT Bombay admissions process. Apply through the IIT Bombay application portal, select CSRE, and mention RIVER Lab and your topic of interest. Information on the admissions process is available on the IIT Bombay research admissions page. The last date to apply is 17 October 2026, extended till 21 October 2026 with a late fee.
For questions, write to pritam.das [at] iitb.ac.in. See the Join page for more about the lab and what we look for.