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Professor Harri Lähdesmäki. The position offers a broad local research network in Bayesian machine learning and computational biology. Your network and team Dr Martinelli is an independent Research Fellow
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. The division is an important part of the eSSENCE e-science collaboration and of the Science for Life Laboratory (SciLifeLab ) network, a national research infrastructure for life sciences. The successful
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of Materials Design and Innovation Posting Number R260134 Posting Link https://www.ubjobs.buffalo.edu/postings/64174 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment Term
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 3 months ago
-driven and physics-informed learning techniques Development of simulation-based optimization methodologies, including Bayesian optimization, derivative-free optimization, multi-objective optimization
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research projects and centers. (See for instance http://www.mn.uio.no/geo/english/about/organisation/geohyd and https://www.mn.uio.no/geo/english/research/groups/remotesensing ). We are a growing, lively
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excellent opportunities to participate in international research networks. We also run an advanced drone lab on behalf of the entire faculty of Mathematics and Natural Sciences (https://www.mn.uio.no/geo
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via nonlinear parametrizations such as deep networks, dynamical systems and control, Bayesian inference and generative modeling, and randomized linear algebra. Applications of interest are transport
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grow. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. Dr Yingzhen Li (https://yingzhenli.net ) and her research group
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that leverage state-of-the-art AI methods (deep learning, generative AI, Bayesian modelling, active learning, etc.) to combine cellular imaging data, chemical compound structure, viral genomes and other omics
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of neural networks, information-theoretic and optimal-transport perspectives on representation and generalisation, probabilistic numerics and Bayesian deep learning, and emerging frameworks for scientific