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Field
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no.: 4644 Explore and teach at the University of Vienna, where over 7,500 academic minds have found a unique blend of freedom and support. Join us if you're driven by a passion for top-notch international
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to develop a holistic e-motor cooling technology, maximising heat transfer through direct-contact, spray cooling. The Team is looking to appoint one Postdoctoral Research Associate on Machine-Learning Assisted
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About the role We wish to appoint an experienced post doctoral researcher to work on an exciting new NIHR-funded study, led by Leeds Beckett University aiming to explore and improve learning
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boundaries. We welcome candidates with a PhD in a relevant discipline and a strong record of research excellence. Enthusiasm for cross-disciplinary research, curiosity-driven problem solving, and the ambition
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for the Research Associate, Grade 7 level, position must have a PhD in a quantitative biology discipline, statistics or machine learning along with a proven track record of research using statistical modelling
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of researchers to develop new stable co-electrocatalysts using high-throughput synthesis and screening and evaluate them for activity and selectivity towards methane or syngas. You will have a PhD in chemistry or
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Leader Requirements Essential & Desirable Knowledge, Skills and Experience: A PhD (or equivalent) in a relevant scientific discipline (e.g. Biology, Chemistry, Engineering, Computer Science) Strong track
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., knowledge representation and reasoning) and bottom-up (e.g., machine learning) methods to study the representation of geographic categories and processes. While we welcome applicants from a broad range of
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34 Faculty of Law Startdate: 01.12.2025 | Working hours: 20 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 30.11.2031 Reference no.: 4930 Explore and teach
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experience in machine learning and image analysis for ultrasound images and video. The successful applicant will possess specialist experience conducting fieldwork, particularly in low-resource or rural