The University at Buffalo is offering immediate openings for one Postdoctoral Researcher and one PhD student in the field of Trustworthy AI and Digital Twins, funded by the National Science Foundation (NSF). The research group, led by Associate Professor Danial Faghihi, focuses on methods-driven research in trustworthy artificial intelligence, digital twins, uncertainty quantification, and scalable algorithms. Applications of this research span healthcare, materials, and engineering systems, emphasizing rigorous computational approaches rather than black-box machine learning. Ideal candidates should 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 interact with experts in applied mathematics, computer science, and domain sciences. Applicants must currently be based in the United States. These positions are supported by NSF funding, ensuring resources for advanced research in cutting-edge topics such as trustworthy AI and digital twins. While specific stipend or tuition details are not provided, the NSF funding indicates a competitive research environment. To apply, interested candidates should email Dr. Danial Faghihi at [email protected] with their CV and a brief statement of interest. For more information, you may visit Dr. Faghihi's LinkedIn profile.

Immediate openings are available for one Postdoctoral Researcher and one PhD student in the lab of Dr. Danial Faghihi, Associate Professor of Mechanical and Aerospace Engineering at the University at Buffalo. The positions are funded by the National Science Foundation (NSF) and focus on research in trustworthy AI, digital twins, uncertainty quantification, and scalable algorithms. The research is methods-driven and not limited to black-box machine learning, with applications spanning healthcare, materials, and engineering systems. Candidates should have strong programming skills and a background in applied mathematics, computer science, or computational engineering. The lab environment is highly collaborative, offering close mentorship and opportunities to interact with collaborators in applied mathematics, computer science, and domain sciences. Applicants must currently be based in the United States. To apply, interested candidates should email Dr. Danial Faghihi at [email protected] with their CV and a brief statement of interest. For more information, see Dr. Faghihi's LinkedIn profile.