The Lin Lab for Intelligent Nexus Systems of Water and Society (LINS Lab) at Clemson University is actively recruiting PhD students for Fall 2026. The lab, led by Assistant Professor Chung-Yi Lin, focuses on the intersection of environmental processes, infrastructure, technology, and human behavior to advance water availability, sustainability, and resilience. Research in the lab spans basin-wide water systems, national data analysis, and integrates computational modeling, decision analytics, data science, and systems thinking.

Potential research areas include water resources planning and management, human–water systems modeling, agent-based modeling, multi-objective optimization, decision analytics, and AI-enabled decision support. The lab also investigates agricultural and urban water use science, including irrigation adoption, water demand dynamics, remote sensing, machine learning, and risk propagation in food–water systems. Another focus is smart and adaptive water systems, such as hydrological digital twins, control and reinforcement learning, cyber-physical resilience, and integrated watershed modeling.

Students joining LINS Lab will have the opportunity to co-develop new research directions as the lab grows. The lab values curiosity, motivation, and technical strength, seeking students who are eager to push the boundaries of water research. Applicants with backgrounds in civil or environmental engineering, computer science, hydrology, agriculture, or related fields are encouraged to apply. Experience in computational modeling, decision analytics, agent-based modeling, optimization, remote sensing, or machine learning is preferred.

Application review is currently ongoing, and interested candidates should submit their applications via the provided form. Prospective students attending AGU 2025 in New Orleans are invited to reach out to Professor Lin for informal discussions about research opportunities. For more information about the lab and its research, visit the LINS Lab website.

No explicit funding details are provided in the announcement. The post does not specify whether the PhD positions are fully funded, partially funded, or self-funded, nor does it mention stipend amounts or tuition coverage.

Key academic keywords include water resources, systems modeling, artificial intelligence, decision analytics, hydrology, agent-based modeling, optimization, remote sensing, machine learning, cyber-physical resilience, and watershed modeling. The opportunity is ideal for students interested in interdisciplinary research at the nexus of environment, technology, and society.