Publisher
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University of Texas at San Antonio

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Postdoctoral Research in AI/ML for Engineering Applications at University of Texas San Antonio University of Texas San Antonio in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available

Deadline

Dec 30, 2026

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Country

United States

University

University of Texas at San Antonio

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Keywords

Computer Science
Mechanical Engineering
Electrical Engineering
Deep Learning
Aerospace Engineering
Mathematics
Artificial Intelligence
Python Programming
High Performance Computing
Engineering Applications
Large Language Models
ML

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About this position

Postdoctoral Research in AI/ML for Engineering Applications at the University of Texas San Antonio (UTSA), United States.

This postdoctoral opening is in NASA-funded research at the Institute of Scientific Research of Air Pollution, focusing on AI, Machine Learning, Large Language Models (LLMs), and Scientific Machine Learning for engineering applications.

Relevant study areas include Computer Science, Mechanical Engineering, Aerospace Engineering, and related fields. Strong programming skills in Python/C++ are required, and experience with PyTorch, Hugging Face, HPC, ROS, CFD, and Scientific AI is highly desirable.

The position offers a competitive salary and university benefits. Applicants must be eligible to legally work in the USA.

To apply, send a CV, cover letter, research statement, and contact details for three references to Prof. Kiran Bhaganagar at [email protected]. Review begins immediately and continues until the position is filled. Closure date listed: 2026-12-30.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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