Postdoc and PhD Positions in Trustworthy AI and Digital Twins at University at Buffalo University at Buffalo in United States

The University at Buffalo is offering immediate openings for one Postdoctoral Researcher and one PhD student in the areas of trustworthy AI and digital twins, funded by the National Science Foundation (NSF). The research group, led by Dr Danial Faghihi, focuses on methods-driven approaches in trustworthy artificial intelligence, digital twins, uncertainty quantification, and scalable algorithms. Applications of this research span healthcare, materials science, and engineering systems, emphasizing rigorous computational methods over black-box machine learning.

Applicants must currently reside in the United States. Ideal candidates will have strong programming skills and a solid background in applied mathematics, computer science, or computational engineering. The lab environment is highly collaborative, offering close mentorship and opportunities to work with experts in applied mathematics, computer science, and domain sciences. This is an excellent opportunity for those interested in advancing research in trustworthy AI and digital twins with real-world applications.

To apply, candidates should email Dr Danial Faghihi ([email protected]) with their CV and a brief statement of interest. The University at Buffalo provides a vibrant research environment and access to NSF-funded projects. No specific deadline is mentioned, so early applications are encouraged.