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and computational fluid dynamics (CFD) Knowledge about physics-informed neural networks (PINNs) Language requirement: Good oral and written communication skills in English English requirements
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part of a team developing analytic likelihood approximations and neural posterior estimation methods for epidemic data analysis. This role offers an excellent opportunity to work at the interface
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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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experience in marine technology and AI will be advantageous Knowledge about high performance computing and computational fluid dynamics (CFD) Knowledge about physics-informed neural networks (PINNs) Language
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applications of neural networks to the analysis of multi-omic data, models for predicting phenotypes using genotype data, biological data integration, etc.. Participation in these projects will include