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Ardavan Yazdanbakhsh

2 weeks ago

PhD Opportunity in Wildfire Research and Data Science at City College of New York City College of New York in United States

Degree Level

PhD

Field of study

Computer Science

Funding

Available

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Country

United States

University

City College of New York

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Keywords

Computer Science
Data Science
Environmental Science
Geography
Civil Engineering
Python Programming
Built Environment
Spatiotemporal Analysis
Statistics

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About this position

PhD opportunity in wildfire research and data science at the City College of New York in the Department of Civil Engineering.

The project focuses on spatiotemporal analysis of large datasets related to wildland fires, with possible directions including modeling wildfire ignition causes using geographic, meteorological, and environmental factors, and studying wildfire impacts on the built environment such as buildings and infrastructure.

This opening sits at the intersection of civil engineering, environmental science, statistics, and data science. Applicants with a bachelor’s degree in Civil Engineering are especially encouraged, but strong candidates from other engineering disciplines, statistics, or computer science are also welcome.

Ideal applicants should have a strong quantitative background and experience with Python, R, or similar tools for data analysis and statistical modeling. The student is expected to begin the PhD program in person at CCNY in Fall 2027.

To apply, contact the professor directly on LinkedIn with your CV and a short note describing your research interests and relevant experience.

Funding details

Available

What's required

Applicants should have a bachelor’s degree in Civil Engineering, or a strong background in another engineering discipline, statistics, or computer science. A strong quantitative foundation is required, along with experience using Python, R, or similar tools for data analysis and statistical modeling. Applicants must be available to begin the PhD program in person at CCNY in Fall 2027.

How to apply

Contact the professor via LinkedIn with your CV and a brief description of your research interests and relevant experience.

More information can be found here

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