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of the developed cavitation model with acoustic radiation models, validating against experimental data. Required Qualifications A relevant educational background within Mathematics, Physics, or Engineering, with a
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already have a Master education) in areas related to(but not limited to) Bayesian deep learning, neural architecture search strategies(e.g. reinforcement-based), confidence estimation in deep neural
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on generative AI have been suggested. The data science team under this project will develop privacy metrics based on Bayesian statistics. The overarching purpose of the legal part of the project is to develop
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science(e.g., mathematics, physics, computer science, etc.), a strong background in data science, statistics, or machine learning, and an interest in biomedicine. Alternatively, a candidate with a