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

Clemson University, in collaboration with the Savannah River National Lab (SRNL, DOE), is offering a Graduate Research Assistant position for a highly motivated MS student interested in modern deep learning applications for water quantity and quality modeling across the Savannah River Basin. This interdisciplinary research project provides hands-on experience in environmental data science, informatics, and artificial intelligence, with a focus on developing predictive models to support risk assessment and emergency decision-making at SRNL.

The selected student will work at both Clemson University and SRNL, gaining exposure to national laboratory research and operations, and may have the opportunity for future employment at SRNL. Research responsibilities include developing and implementing physics-informed deep learning architectures for water modeling, collecting and analyzing hydrologic and water quality data from various sources, benchmarking models, and collaborating with researchers from both institutions. The student will also participate in weekly meetings, present findings at conferences, and co-author manuscripts.

Applicants must be U.S. citizens and hold a bachelor's degree in civil/water resources engineering, environmental engineering, computer science, or a related field. Required skills include strong programming abilities in Python and C++, familiarity with deep learning frameworks (TensorFlow, PyTorch), and an interest in water and environmental modeling and AI applications. The ability to work collaboratively in a multidisciplinary team, along with strong analytical, problem-solving, and communication skills, is essential. A minimum GPA of 3.4 (on a 4.0 scale) and GRE scores are mandatory for application.

To apply, candidates should submit a single PDF containing contact information, highest degree earned, language proficiency, GPA and GRE scores, contact details for 2–3 references, a cover letter detailing research background and motivation, a curriculum vitae, and an unofficial transcript to [email protected]. The application deadline is April 10, 2026, at 5:00 PM EDT, but the position will remain open until filled.

This opportunity is ideal for students interested in deep learning, water modeling, environmental data science, hydrology, and AI, and offers a pathway to gain valuable research and professional experience in collaboration with a leading national laboratory.