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 and sustainability.

The research aims to develop next-generation, data-driven and physics-guided frameworks to improve the performance, durability, and resilience of civil infrastructure systems. The materials focus includes asphalt and cementitious systems, making this a strong fit for students interested in civil engineering, materials science, and computational methods for infrastructure.

Preferred preparation includes a background in Civil Engineering, Materials, or related fields. Experience with data analytics or machine learning is preferred but not required, and Python programming skills are mentioned as useful.

This is an academic recruitment post from Assistant Professor Ali Behnood at the University of Mississippi in the United States. No deadline, funding package, or formal application portal is provided in the post. Interested candidates are asked to reach out directly and share a CV.