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Yuki Miura

1 month ago

AI-driven methods for climate and infrastructure risk mitigation NYU Tandon School of Engineering in United States

I am recruiting PhD students to join my lab in climate, energy, and risk analytics at NYU.

New York University

United States

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Keywords

Computer Science
Data Science
Environmental Science
Mechanical Engineering
Aerospace Engineering
Risk Assessment
Network Analysis
Artificial Intelligence
Energy Engineering
Earth Science
Reinforcement Learning
Climate Resilience
Urban Geography

Description

The Climate, Energy, and Risk Analytics (CERA) Lab at NYU Tandon School of Engineering, led by Assistant Professor Yuki Miura, is recruiting fully-funded PhD students for Spring or Fall 2026. The lab focuses on developing AI-driven methods to understand, quantify, and mitigate climate and infrastructure risks, bridging physics, data science, and policy for real-world impact in collaboration with city stakeholders. Research areas include large language models (LLMs) for risk perception and financial signals, vision-language models (VLMs) for global exposure mapping, cascading impact and network modeling, and reinforcement learning for adaptation planning. Candidates should have strong quantitative skills and backgrounds in engineering, risk analysis, or data science. Successful applicants will receive full funding, including tuition, stipend, and health insurance. The application deadline is November 30, 2025. Interested candidates should review the provided PDF for detailed instructions and submit their applications before the deadline. The opportunity is ideal for students passionate about data-driven climate risk research and interdisciplinary collaboration.

Funding

Successful applicants will receive full funding, including tuition, stipend, and health insurance.

How to apply

Review the PDF for detailed application instructions. Prepare your application materials and submit them before the November 30, 2025 deadline. Contact the lab or department for further details if needed.

Requirements

Applicants should be motivated and quantitatively strong, with backgrounds in engineering, risk analysis, or data science. No specific GPA or language test requirements are mentioned, but strong quantitative skills and motivation for climate risk research are preferred.

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