土木/机械工程, 数据科学, 机器学习 博士招生
9630
The Uncertainty Quantification (UQ) Lab at the University of Houston, led by Dr. Ruda Zhang, invites applications for two (2) PhD student positions in areas of data-driven engineering and uncertainty quantification. The expected start time is Fall 2022 (classes start on August 22, 2022) and may extend into Spring 2023. Applications are accepted until May 15, 2022; but late submissions may be considered. Interested students should fill out this Google form (forms.gle) as soon as possible to expedite the screening process. Official applications must be submitted according to university guidelines (cive.uh.edu).
Research projects will be determined based on student interests and background. Prospective students are encouraged to read the research overview (ruda.city). Some research topics of interest include: digital twins for structural systems; infrastructure health monitoring; UQ for material systems; deep learning tools designed for engineering; quantitative sustainability and resilience.
The UQ Lab at UH welcomes members from diverse academic backgrounds. Preferred skills/experiences include: coursework in mechanics, mathematics, or physics; computer programming (Python, etc.); research in engineering/computational mechanics, deep learning; English presentation and writing.
Successful applicants will receive full tuition support and stipend for the duration of their study. Besides, the Lab will provide extra financial support for conferences, training workshops, and summer internships.
For details of these positions, see ruda.city
Research projects will be determined based on student interests and background. Prospective students are encouraged to read the research overview (ruda.city). Some research topics of interest include: digital twins for structural systems; infrastructure health monitoring; UQ for material systems; deep learning tools designed for engineering; quantitative sustainability and resilience.
The UQ Lab at UH welcomes members from diverse academic backgrounds. Preferred skills/experiences include: coursework in mechanics, mathematics, or physics; computer programming (Python, etc.); research in engineering/computational mechanics, deep learning; English presentation and writing.
Successful applicants will receive full tuition support and stipend for the duration of their study. Besides, the Lab will provide extra financial support for conferences, training workshops, and summer internships.
For details of these positions, see ruda.city
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