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Tenure-Track Assistant Professor at the Graduate School of Pharmaceutical Studies, Tohoku University
research approaches, including but not limited to those that leverage emerging technologies—such as AI-based analysis, computational science, and iPS cell-based drug discovery models—to identify novel drug
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of information theory, mathematical modeling and machine learning and their application to medical science problems (5) Deep Learning in Biomedical Sciences (6) Theory and methods on prediction, control and
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Mathematical Science. We welcome applications from researchers with an interest in any of the following fields: quantum gravity, field theory, machine learning, statistical physics, random matrix theory
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[Work content and job description] Related to digital scent technology, human interface (olfactory displays and/or olfactory games), Data science (multidimensional data analysis and machine learning
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Millimetre wave Electromagnetic simulation We also welcome researchers from different fields: AI (machine learning, big data, etc) Semiconductors As a minimum requirement, you must have a PhD degree in
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simulation or machine learning of soft and biological matter, e.g. Monte Carlo, molecular dynamics and finite element computer simulations. Origins of life research involving topology and chirality
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Computation and Adaptation , RIKEN Center for Brain Science (Laboratory Head: Taro Toyoizumi) Medical Data Deep Learning Team , Advanced Data Science Project , RIKEN Information R&D and Strategy Headquarters
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Millimetre wave Electromagnetic simulation We also welcome researchers from different fields: AI (machine learning, big database, etc) Semiconductors As a minimum requirement, you must have a PhD degree in
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researchers in the KMI Flavor Physics International Research Center (FlaP) to work on cross-disciplinary research on the application of machine-learning & AI techniques to researches on flavor physics (high
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, Learning Theory, Biology, etc. The main areas of interest include (but are not restricted to) the following: - information measures; - concentration of measure; - concentration of measure in non-classical