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equivalencies: https://hr.uky.edu/employment/working-uk/equivalencies Required Related Experience No experience required. Required License/Registration/Certification Have one or more of the following: 1. Kentucky
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: https://hr.uky.edu/employment/working-uk/equivalencies Required Related Experience No experience required. Required License/Registration/Certification Have one or more of the following: 1. Kentucky
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incorporate optimized machine learning algorithms, support standardized IoT protocols, and be validated in laboratory and semi-industrial environments. The project contributes to smart maintenance strategies
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Chekouo and his collaborators within and outside the University of Minnesota. The research will focus on the development of Bayesian statistical/machine learning methods for the data integration analysis
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- Maintain files (creating, updating, and organizing). - Student Assistant will perform other duties and responsibilities as assigned by overseeing Faculty. Minimum Qualifications: Ability to learn and perform
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expertise across autonomy, machine learning-based control, multi-agent systems and Decision-making. Excellent communication skills (both written and oral) with ability to communicate complex and conceptual
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inference, and Machine Learning methods. In addition to leading their own research projects, the appointed candidate will have the opportunity to contribute to the projects of PhD students in the group, as
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Range $15.30-24.50/hour Type of Position Staff Position Time Status Full-Time Required Education BS Click here for more information about equivalencies: https://hr.uky.edu/employment/working-uk
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular
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apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular dynamics (MD) simulations