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for renewal for an additional term based on institutional needs. Visiting Lecturers carry a 5-5 teaching load. We seek to hire a candidate with strong teaching credentials to teach our introductory course in
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, speaking); French is a plus but not mandatory. - Strong background in ecology. - Experience with statistical analysis using R; interest in machine learning is an asset. - Prior experience with one or more of
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position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic
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methods at the intersection of statistics and machine learning. Collaboration, both within the Department and across the university, is a core value of the Department and a hallmark of the research work
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the application of these methods to problems in the physics of oxides, semiconductors, metals and their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists
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quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not mandatory. Excellent written and
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open PhD positions throughout the year. Learn more about PhD opportunities at the Hertie School and the relevant application deadlines here . Further information on the application procedure can be found
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of computational methods that enable machines to perform tasks requiring perception, learning, reasoning, and decision-making. It encompasses core areas such as machine learning, data-driven modeling, intelligent
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Job description: DESY The CMS Quantum Computing group develops generative machine learning models for detector simulations, specifically the simulation of showers in calorimeters: Proof-of-principle
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of the ERC Consolidator project AUTOMATIX (see details below), we are seeking a PhD candidate to develop machine learning approaches for constitutive modeling. Context With the advent of machine-learning (ML