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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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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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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
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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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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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, technical depth, and a strong track record of applied research in Computational Biology, Structural Biology, Protein Engineering, Machine Learning, or a closely related field. Strong understanding and
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for a dedicated PhD student to join our team. Find more information about the Strategic Management area and its members here: http://strategy.univie.ac.at What you will be doing: In
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to teach in at least one of the thematic areas listed above. Additional desired qualifications include a PhD degree, the ability to teach across multiple areas of the curriculum, strong engagement with
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Advanced brain-computer interface School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications accepted all year round