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Job Description Are you interested in uncovering the mechanisms underlying human social dynamics between dyads, groups, and networks, during real-time social interaction? We invite applications
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machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and
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machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and
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regulatory networks that are active in blood cells in health and disease. The successful candidates will have a PhD in Bioinformatics, Computational Biology, Biostatistics or in a related quantitative field
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, scheduling and operations of complex systems. This topic will pursue integrated, holistic planning and scheduling to optimize resilience across several factory systems. Development of AI-based tools and
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characterization (e.g. NMR), biofilm extracellular polymeric substances, biophysics, glycoconjugates, complex assembly, or lectins, is an advantage. Your profile Applicants should hold a PhD in glycobiology
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on developing machine-learning-based or statistical emulators to approximate key outputs of complex Earth System Models, with the aim of enabling efficient uncertainty quantification, sensitivity analysis, and
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cell transitions accelerates muscle regeneration in young & aged mice. Cell Report Medicine, Aug 2023. A complex epigenome-splicing crosstalk governs epithelial to mesenchymal transition in metastasis