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familiarity with supercomputing or cloud platforms. Experience with AI/deep learning beyond simple tools (e.g., Random Forest, ANN), particularly in integrating physical models and AI algorithms. Knowledge
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of the following backgrounds are particularly encouraged to apply: Machine learning and deep learning, particularly for time-series modeling Structural health monitoring (SHM), including fiber-optic sensor
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the interfacial transition zone, - adjustment of rheological properties through tuning of concentrations and types of viscosity modifiers and superplasticizers, - deep learning modeling
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origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http
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in the University of Minnesota. The research will focus on applying, developing and implementing novel statistical methods for causal inference, integrative data analysis or/and machine/deep learning
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per annum (Level A6 to Level B3) plus 17% superannuation. About You You will have completed a PhD in mechatronics or instrumentation, or in a closely related discipline. You will have deep and broad
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a 3-year DOE-sponsored project that started in September 2024. The Postdoctoral Research Associate working on P1 will develop and test deep learning algorithms for model emulation and model parameter