💼 Job
Apply for the NYU Fully Funded PhD Opportunities in Climate, Energy and Infrastructure Analytics 2027 (full tuition coverage + competitive PhD stipend) - Global South Opportunities
About this opportunity
Aspiring researchers interested in artificial intelligence, climate change, infrastructure resilience, remote sensing, machine learning, and risk analytics have an opportunity to pursue fully funded doctoral research at New York University (NYU).
The Climate, Energy, and Risk Analytics (CERA) Lab at NYU is seeking highly motivated PhD students for Spring 2027 and Fall 2027 entry. The opportunity is affiliated with the Department of Mechanical and Aerospace Engineering (MAE), the Center for Urban Science and Progress (CUSP), and the NYU Tandon School of Engineering.
Successful candidates will receive full tuition coverage, a competitive PhD stipend, comprehensive health insurance, and research and conference support.
The position is particularly relevant for students from quantitative and interdisciplinary backgrounds who want to work on challenging research questions at the intersection of engineering, artificial intelligence, climate risk, complex systems, and societal resilience.
Requirements
Who Should Apply?
The CERA Lab is looking for students who are highly motivated, intellectually curious, and comfortable working on challenging and open-ended research problems.
Strong candidates may demonstrate some combination of:
• Strong quantitative and analytical skills
• Independent coding experience
• Previous research experience
• Interest in real-world systems and societal impact
• Ability to work across disciplines
• Curiosity and initiative
• Resilience when facing challenging research problems
Prior publications are encouraged but are not required.
Relevant academic and technical backgrounds may include:
• Mechanical engineering
• Computer science
• Civil engineering
• Environmental engineering
• Applied mathematics
• Applied physics
• Operations research
• Data science
• Statistics
• Computational social science
• Other related quantitative disciplines