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September 2027, with some flexibility upon agreement. - A PhD in Mathematics (completed by the start date) is required. Profile We welcome applications from highly motivated candidates with a background in
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microscopy. • Expertise in metabolomics with mass spectrometry is desired. • Strong general computer skills, experience with databases and scientific applications, and ability to quickly learn and master
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technologies. The candidate will work at the intersection of Artificial Intelligence, Scientific Machine Learning, and Energy Materials, contributing to the design of self-driving laboratories and no-code
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will join a research group working on longitudinal models of multiple chronic diseases across the life course. The postdoctoral researcher will contribute to building and evaluating machine learning
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. The successful applicant will possess a PhD or equivalent doctoral degree in the social sciences, including political science, public policy, political ecology, law, geography or another relevant field with some
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(postdoc) Limited until: 31.10.2032 Reference no.: 6212 There are many good reasons to want to research and teach at the University of Vienna. And one is why around 7,700 academic staff members before you
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mechanics, machine learning or applied/computational mathematics. ● Demonstrated ability to carry out original mathematical derivations and/or develop computational tools, evidenced by publications
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improve high-throughput experimental workflows including closed-loop thin-film optimization Apply AI and Machine Learning for data analysis and modelling Develop, improve and implement HW/SW concepts and
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The Applied Mathematics and Computational Research Division at Lawrence Berkeley National Laboratory (Berkeley Lab) is seeking a Postdoctoral Researcher – Scientific Machine Learning & Computational
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are also available. Applicants must have, or be about to obtain, a PhD in materials science, physics, or related discipline with experience in the design and conduct of experiments. Some experience with