There is an immediate opening for a Ph.D. student in the UQLID (Uncertainty Quan- tification, Learning, Inference, and Design) Lab in the Department of Mechanical Engineering at Northern Arizona University to work on “Scientific Machine Learn- ing (SciML).”
The position is fully funded with a monthly stipend and support for conference and workshop travels. Interested individuals with a Bachelor’s or Master’s Degree in Mechanical, Civil, Aerospace Engineering, or Engineering Mechanics, experience in one or more of the following topics, and good verbal and written communication skills are encouraged to email Dr. Subhayan De (Subhayan.De@nau.edu) with a current CV attached as soon as possible.
Preferred Expertise:
- Scientific machine learning (SciML),
- Multi-fidelity methods,
- Computational mechanics, and
- Uncertainty quantification.
For more information, please visit the following web pages: UQLID Lab, Ph.D. in Mechanical Engineering at NAU, and NAU Graduate Admissions.
Northern Arizona University is an equal opportunity/affirmative action employer. Women, minorities, individuals with disabilities, and protected veterans are encouraged to apply.
Department of Mechanical Engineering
Northern Arizona University
Flagstaff, Arizona
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