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description The candidate will work on problems at the intersection of mathematical statistics, machine learning, and generative modeling, particularly for sequential data arising in complex dynamical systems
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to build sequence dependent predictive deep learning models, and physical mechanistic models (thermodynamic and kinetic models etc.). Examples of suitable backgrounds: machine learning, programming
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