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Dylan Blaskey

1 year ago

Regional water quality modeling University of South Carolina in United States

Degree Level

PhD

Field of study

Computer Science

Funding

The position is fully funded for the PhD student, starting Fall 2026. No specific stipend amount or tuition details are provided.

Deadline

Dec 28, 2026

Country flag

Country

United States

University

University of South Carolina

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Keywords

Computer Science
Machine Learning
Environmental Science
Hydrology
Earth Science
Python Programming
Regional Economics
Water Pollution

About this position

The Integrated Systems Hydrology Lab at the University of South Carolina is recruiting a fully funded PhD student to begin in Fall 2026. The research focuses on regional water quality modeling, with an emphasis on computational hydrology, mechanistic models, and machine learning approaches. The successful candidate will study water quality across South Carolina and beyond, using quantitative methods and tools such as Python and hydrologic modeling.

The lab offers a collaborative, multidisciplinary environment and opportunities to engage with the Institute for Clean Water, a partnership between USC and the South Carolina Department of Environmental Services. Applicants should be highly motivated, possess strong quantitative skills, and have experience or interest in Python, machine learning, and hydrologic modeling.

Funding is fully provided, but specific financial details are not listed. Interested candidates should email Dylan Blaskey with their CV and a brief description of their background and research interests. More information is available on the lab website.

Funding details

The position is fully funded for the PhD student, starting Fall 2026. No specific stipend amount or tuition details are provided.

What's required

Applicants should be highly motivated and interested in computational hydrology, with a focus on mechanistic and machine learning models for water quality. Strong quantitative skills are required, and experience or interest in Python, machine learning, and hydrologic modeling is especially welcome. No specific GPA, language test, or degree requirements are mentioned, but a background relevant to hydrology or environmental science is implied.

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Professors

Assistant Professor at University of South Carolina

University Name
Country flag

United States

Research Interests

Hydrology

Computer Science

Water Pollution

Machine Learning

Earth Science