The Soft Tissue Biomechanics Laboratory and the Fuhg Research Group in the Department of Aerospace Engineering and Engineering Mechanics at The University of Texas at Austin are seeking a postdoctoral fellow in computational engineering and machine learning, with a start date in Spring or Summer 2026. This opportunity is ideal for researchers interested in the intersection of machine learning, computational engineering, biomechanics, and medical imaging.

The position focuses on integrating physics-based modeling, medical imaging, and scientific machine learning to study complex soft tissues. The successful candidate will develop computational frameworks that connect imaging data with tissue mechanics, contributing to patient-specific modeling, inverse methods, and next-generation digital biomechanics tools. The research environment is highly interdisciplinary, offering opportunities to work on innovative data-driven modeling frameworks and collaborate with leading experts in biomechanics, AI, and computational science.

Applicants should hold a Ph.D. in Aerospace Engineering, Mechanical Engineering, Engineering Mechanics, Computational Engineering, Bioengineering, or a related field. Priority will be given to candidates with interests in image recognition, computational engineering, and machine learning. Strong experience with Python or C++ is highly desirable. The position is supervised by Assistant Professor Jan Niklas Fuhg and Dr. Manuel Rausch, both affiliated with The University of Texas at Austin.

UT Austin is a top-ranked research university located in Austin, Texas, a city known for its vibrant tech industry and high quality of life. The Department of Aerospace Engineering and Engineering Mechanics is recognized for its excellence in research and education, providing a stimulating environment for postdoctoral researchers.

To apply, interested candidates should email Jan Fuhg at [email protected] with a brief description of their research interests and a CV. The position is expected to be filled by August 2026. For more information about the research groups and the university, please refer to the provided LinkedIn profiles and university website.