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source

Howard University

PhD Position in Civil & Environmental Engineering (Environmental Informatics, Hydrology) at Howard University Howard University in United States

Degree Level

PhD

Field of study

Machine Learning

Funding

Available

Deadline

Apr 15, 2026

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Country

United States

University

Howard University

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Keywords

Machine Learning
Environmental Science
Chemical Engineering
Remote Sensing
Environmental Engineering
Hydrology
Civil Engineering
Geoinformatics
Data-driven Modeling
Emerging Contaminants

About this position

Howard University is offering a PhD position in Civil & Environmental Engineering, with a focus on environmental informatics, hydrology, data-driven modeling, and emerging contaminants. The successful candidate will join the research group led by Dr. Sanjib Sharma and Dr. Sara Kamanmalek at Howard University, an R1 HBCU located in Washington, D.C. This interdisciplinary opportunity is ideal for students interested in applying advanced data analytics, GIS, remote sensing, and machine learning to environmental and hydrological challenges.

Applicants should hold a master's degree in Environmental, Civil, or Chemical Engineering, or a closely related field. Experience with environmental data, watershed modeling, or climate data is required, along with programming skills in Python, R, MATLAB, or similar languages. Skills in GIS, remote sensing, and data analytics are highly valued. International applicants must provide TOEFL scores.

Applications are reviewed on a rolling basis, but the official deadline for Fall 2026 admission is April 15, 2026. To apply, candidates should submit a single PDF containing their CV, research statement, and contact information for references to both Dr. Sara Kamanmalek and Dr. Sanjib Sharma via email. This is an excellent opportunity to develop impactful, interdisciplinary research in a supportive academic environment at Howard University's College of Engineering and Architecture.

Funding details

Available

What's required

Applicants should have a master's degree in Environmental, Civil, Chemical Engineering, or a related field. Experience with environmental data, watershed modeling, or climate data is required. Skills in GIS, remote sensing, data analytics, or machine learning are preferred. Programming experience in Python, R, MATLAB, etc., is expected. International applicants must provide TOEFL scores.

How to apply

Prepare a single PDF with your CV, research statement, and references' contact information. Email the PDF to [email protected] and [email protected]. Applications are reviewed on a rolling basis. Official deadline is April 15, 2026.

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