Suraj Bhagat
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Fully Funded PhD in Computer Science, Environmental Data Science, and Climate Intelligence SRM University–AP in India
Degree Level
PhD
Field of study
Computer Science
Funding
Fully funded PhD positions are offered.
Deadline
Oct 20, 2026
Country
India
University
SRM University-AP

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About this position
PhD opportunity at SRM University–AP, Amaravati in the intersection of Computer Science, Environmental Data Science, and Climate Intelligence.
The position is focused on AI/ML and advanced soft computing for environmental and climate applications. Research themes include climate intelligence and climate risk analytics, AI for water resources and hydrological systems, climate data analysis and extreme event prediction, remote sensing, GIS and geospatial AI, environmental monitoring and sustainable agriculture, time-series forecasting and predictive analytics, explainable AI, deep learning, and digital twins/decision support systems for environmental sustainability.
This is a fully funded PhD opening. The post is especially suitable for candidates with a background in Computer Science, Information Technology, Data Science, AI/ML, or related disciplines who want to apply computational methods to real-world environmental and climate challenges.
Eligibility highlights: M.Tech/MSc/M.E. or equivalent in a relevant field; strong interest in programming, machine learning, and computational modelling; desirable skills include Python/R, statistical modelling, deep learning, geospatial analytics, and time-series analysis. An environmental science background is not required.
How to apply: Email Dr Suraj Bhagat with your CV and a brief description of your research interests. The post asks interested candidates to reach out before 20 Oct 2026.
Funding details
Fully funded PhD positions are offered.
What's required
Applicants should have an M.Tech, MSc, M.E., or equivalent in Computer Science, Information Technology, Data Science, AI/ML, or related fields. Strong interest in applying programming, machine learning, and computational methods to environmental and climate-related problems is required. Knowledge of Python/R, statistical modelling, deep learning, geospatial analytics, or time-series analysis is desirable. Motivation for interdisciplinary research, scientific writing, and high-impact publications is expected. An Environmental Science background is not required.
How to apply
Interested candidates should contact Dr Suraj Bhagat by email with a CV and a brief description of their research interests. Reach out before 20 Oct 2026.
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