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from blood and redirected toward cancer antigens via gene-engineering with chimeric antigen receptors (CARs) or T cell receptors (TCRs). CAR-T cell therapy has elicited profound responses in
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the Medical College of Wisconsin Cancer Center that is supportive and favorable to learning, and includes opportunities to interact with peers, graduate students, postdoctoral researchers, and other
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for developing machine learning models for the automatic identification of species from images collected through electronic monitoring systems (Work Package 3 – Bycatch Monitoring). The candidate will be involved
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. Researching and developing novel machine learning architectures for integration across multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and
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/Research Fellow(SRF/RF) to carry out research in robotics and machine learning by exploring cutting-edge approaches such as learning-based robot perception, adaptive control with reinforcement learning
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assimilation, machine learning, and seasonal weather forecasts. As a Postdoctoral Research Fellow, you will play a crucial role in developing and testing statistical models for the accurate forecasting
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research and recent publications, see the Geometric Machine Learning Group’s website: https://weber.seas.harvard.edu/ . For questions, please email mweber@seas.harvard.edu Applications will be reviewed on a
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Matter Physics o Physical Chemistry and Theoretical Chemistry o Combinatorics, Algorithm, Extremal Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and
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experimental data from both literature and in-house experiment results Use state-of-the-art machine learning models to develop a multi-scale droplets evaporation model Assists in co-supervision of Final Year
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Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and Quantum Algorithm for Computational Quantum Many-body Theory o Theory and Computation of Correlated