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Elhoseiny, Code: https://github.com/yli1/CLCL Uncertainty-guided Continual Learning with Bayesian Neural Networks (ICLR’20), Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach, Code: https
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in the design, processing, and characterization of advanced semiconductors — including organic, hybrid, and 2D materials. Applicants should demonstrate a strong track record of fundamental and applied
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the surrogate forward models with a Bayesian inverse modeling framework to achieve real-time or near-real-time uncertainty quantification, such that we can efficiently resolve the uncertainties rising from rock
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, Uncertainty quantification, Approximation Theory, Applied Probability and Bayesian statistics, Optimal Control and Dynamic Programming. Appointment, salary, and benefits. The appointment period is two years
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and strategic partnerships. Essential Qualifications: Ph.D. degree obtained within the last 2-3 years, and possessing a strong track record of research excellence. Candidates nearing completion
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be considered. Successful candidates should hold a Ph.D. in Biological Sciences or a related field, with a robust track record of publications in top-tier journals, and must be eager to pioneer