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postdoctoral experience; Demonstrated research record that combines Artificial Intelligence and/or Machine Learning with one or more of the following areas: Scientific Computing, Modeling & Simulation
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molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. Importantly, mastery of the experimental and theoretical aspects shall equip doctoral
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mathematical foundations of data science, machine learning and/or artificial intelligence. Preference will be given to candidates studying either the application of data science/ML/AI to problems in
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topics. Experience developing software in a scientific computing context, ideally using Python/Pytorch/R, including the use of established libraries used in data science and artificial intelligence
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or artificial intelligence; • A good team spirit and willingness to collaborate; • Very good command of the English language. These skills would be an advantage: • Experience with Lagrangian transport
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Professorial Research Fellow in Artificial Intelligence (AI) and Machine Learning (ML) to provide leadership and vision in advancing research excellence. This is a unique opportunity to apply cutting-edge
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engage in data-driven, computational, and/or pluridisciplinary approaches to cultural, literary, or visual analysis. Other research areas of interest include cultural analytics, artificial intelligence
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to apply. These methodologies include, but are not limited to, applying artificial intelligence approaches to large molecular, imaging, and/or clinical datasets to understand and transform brain health
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solutions for pressing societal challenges (e.g. communication, artificial intelligence, climate protection, health, etc.) through modern electronic & photonic technologies. The work covers the entire
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attracted more than $1.4 billion in research awards this past year in fields ranging from biomedical technology to artificial intelligence, energy, sustainability, semiconductors, neuroscience, and national