Dr. Jinlong Wu in the Department of Mechanical Engineering at UW-Madison is looking for two Ph.D. students (the anticipated starting term is 2023 Spring/Fall) in research areas of Scientific Machine Learning, Data Assimilation, and Uncertainty Quantification with the focus on (i) developing novel data-driven modeling and simulation techniques, and (ii) applying them to building digital twins for engineering applications (e.g., renewable energy systems, advanced manufacturing, autonomous systems). Students will be supported by research assistantships that cover the full tuition and stipend. For those who are interested, please send your CV and transcripts to jinlong.wu@wisc.edu.
Required qualifications:
Bachelor/Master degree in engineering, applied math, or a related field.
Preferred qualifications:
Passionate about Scientific Machine Learning/Data Assimilation/Uncertainty Quantification.
Previous experiences with research projects of computational fluid dynamics (or projects of computational physics in general).
Strong coding skills in one or more programming languages (Python/Julia/C/C++).
Solid background in undergraduate-level math and statistics courses.
Proficiency in English reading, writing, and speaking.
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