Publisher
source

Danial Faghihi

1 month ago

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

Degree Level

PhD, Postdoc

Field of study

Computer Science

Funding

The positions are funded by NSF projects. No specific stipend or tuition details are provided.

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Country

United States

University

University at Buffalo

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Where to contact

Official Email

Keywords

Computer Science
Mathematics
Uncertainty Analysis
Metamaterial
Applied Mathematic
Digital Twins

About this position

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.

Funding details

The positions are funded by NSF projects. No specific stipend or tuition details are provided.

What's required

Applicants must be currently based in the U.S. Candidates should have strong programming skills and a background in applied mathematics, computer science, or computational engineering. Collaborative skills and interest in trustworthy AI, digital twins, and scalable algorithms are preferred.

How to apply

Email Dr. Danial Faghihi at [email protected] with your CV and a brief statement of interest.

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