The Reliability and Design Automation (RaDA) lab at UTD is inviting creative, motivated and open-mind Ph.D., Master and Undergraduate candidates in any science and engineering departments to join us, as long as you have interests and can fit the projects in our lab.
Our objective is to study and create AI and machine learning methods for engineering design, with the goal of solving the most challenging design problems including high-dimensional problems, design under uncertainty, and novel design discovery. Our research is interdisciplinary. Candidates with interests in the following areas are encouraged to apply.
- Predictive modeling and Physics-informed machine learning
- Reliability analysis and uncertainty quantification
- Design under uncertainty and stochastic optimization
- Failure prognostics and health management
If you are interested in joining us, please send Prof. Xu (email: yanwen.xu@utdallas.edu) the following documents:
Your full CV (with GPA, and TOEFL scores; working experiences; publications), and electronic copy of transcripts;
Qualifications:
- B.S. or M.S. in Mechanical Engineering, Industrial Engineering, Computer Science, or a closely related field.
- No unexplained gaps in the CV
- Programming skills in Python and MATLAB.
- Experience in conducting Finite Element Analysis.
- Knowledge of statistical analysis, data mining, and machine learning is preferred.
- Self-motivated, strong interests in coding and quantitative methods.
Dr. Xu’s group also provides research opportunities for undergraduate and master students. If you are interested in programming and simulation, please contact Dr. Xu for more details.
Prerequisites for undergraduate researcher:
- Coursework on partial differential equations and linear algebra.
- Experiences in Python or MATLAB programming.
- Coursework on statistics is a plus.
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