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Field
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important pathogens. About you The successful candidate will develop and apply genome analysis pipelines to identify potentiating mutations and/or gene gains on projects across the IOI and PubMLST network
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computational methods in the fields of theoretical chemistry/physics, particularly for molecular quantum dynamics, electron dynamics and/or tensor network states. Applicants are not expected to have prior
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multiscale network structure. The researcher will develop scalable methods for computing these features on a very large knowledge graph, integrate them into a transformer-based language model, and test their
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on the mathematical theory of deep learning as part of the joint NSF-EPSRC project “DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | 3 days ago
Job Offer from September 17, 2026 The “Computational Relativistic Astrophysics" division at the Max Planck Institute for Gravitational Physics (Albert Einstein Institute; AEI) in Potsdam, led by
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programme Collaboration with Stanford University and the global LITE network Advanced training in quantitative proteomics and computational biology Relocation support and eligibility for LITE Care & Career
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-science ) carries out research on chemistry and its applications at an international level and provides academic teaching based on high quality research. The Department of Computer Science is a leading unit
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network discovery and individualized circuit targeting, multimodal concurrent brain stimulation-recording, and computational modeling. We bridge invasive approaches, including intracranial electrical
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and Social Policy, the Health and Social Services Management Major and co-host the Social and Public Policy Studies Major with the Department of Economics. The Department hosts an MSocSc Programme in
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develop and optimize scientific and engineering applications leveraging high-speed network capability provided by the Energy Sciences Network or run on next-generation high performance computing and data