Graduate Research Assistant (MS) in Deep Learning for Water Modeling at Clemson University Clemson University in United States

Clemson University’s Department of Environmental Engineering and Earth Sciences, in collaboration with Savannah River National Lab (SRNL), is offering an exciting Graduate Research Assistantship for a motivated MS student. The research focuses on modern deep learning applications for water quantity and quality modeling across the Savannah River Basin. The selected student will gain hands-on experience in environmental data science, informatics, and artificial intelligence, contributing to predictive models that support risk assessment and emergency decision-making at SRNL.

The position is interdisciplinary, with potential admission to either Clemson’s Agricultural Systems Management or Computer Science graduate programs, depending on the candidate’s background. The research will be conducted both at Clemson University and SRNL, providing valuable exposure to national laboratory research and operations, and may lead to future employment opportunities at SRNL.

Responsibilities include developing and implementing physics-informed deep learning architectures for water modeling, collecting and analyzing hydrologic and water quality data, benchmarking models, participating in research meetings, presenting findings, and collaborating with researchers from both institutions. The ideal candidate will have a strong background in civil or environmental engineering, computer science, or a related field, with demonstrated programming skills in Python and C++, and familiarity with deep learning frameworks such as TensorFlow or PyTorch. Interest in water and environmental modeling, as well as AI applications, is essential.

Applicants must be U.S. citizens and have a minimum GPA of 3.4 (on a 4.0 scale), with GRE scores required. Application materials should include contact information, degree details, GPA and GRE scores, references, a cover letter, CV, and unofficial transcript. The deadline for applications is April 10, 2026, at 5:00 PM EDT, but the position will remain open until filled. For more information, visit the department’s LinkedIn page or contact [email protected].