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scientific machine learning, knowledge of atmospheric dynamics, new observations, and close connections with national meteorological services, as well as several leading weather forecasting centers and tech
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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning for improving
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dynein, which power the movement of membranes and chromosomes along microtubules inside cells, and also plans to explore how these and other cellular molecular machines adapt to extreme temperature
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all areas of computational chemistry and machine learning related to that area to join our vibrant, collaborative, and supportive discovery research community at the Mission Bay Campus in San Francisco
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implementing computational schemes for ODE and / or PDE based models Ideally experience with machine learning methods for identifying governing equations from experimental observations (e.g., https://github.com
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think outside the box, to learn fast, collaborate effectively, iterate quickly, and work at the interface of both experimental and computational design. Qualifications for Computer Scientists, AI/ML: PhD
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work can be found by visiting https://federlab.github.io/ About the Postdoctoral Scientist role: This role is an ideal fit for an intellectually curious, creative, and driven scientist ready to gain
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catalysts for the synthesis of a range of industrially valuable compounds. This PhD project is part of the Horizon Europe Marie Sklodowska-Curie Action (MSCA) doctoral network (DN) ELEGANCE (machinE LEarning
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polar orbit, passing near the poles about 15 times per day and regularly observing the CIFAR study region. Its payload - two optical cameras, a thermal camera, and onboard machine-learning capabilities
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the Tenure Track position, such as Machine Learning, Neural Networks, Optimization, Applied Harmonic Analysis, Inverse Problems, Quantum Information, and other relevant areas. Additionally, the position will