PhD Position in Physics-Informed AI for Infrastructure Materials and Digital Twins University of Mississippi in United States

The University of Mississippi research group led by Ali Behnood is seeking a highly motivated PhD student to join a project at the intersection of physics-informed AI, infrastructure materials, digital twins, uncertainty-aware prediction, and climate resilience.

This opportunity is especially relevant for students interested in civil engineering, materials science, and data-driven modeling for sustainable infrastructure. The research will focus on next-generation, data-driven and physics-guided frameworks to improve the performance, durability, and resilience of civil infrastructure systems, including asphalt and cementitious materials.

Preferred preparation includes a background in Civil Engineering, Materials, or a related field. Experience with data analytics or machine learning is helpful but not required, and programming skills such as Python are valued.

This is a PhD opening at the University of Mississippi in the United States. No deadline or formal application portal is mentioned in the post; interested candidates are asked to contact the professor directly and share a CV.