485 programming-"the"-"DAAD"-"IMPRS-ML"-"U"-"Durham-University"-"U.S"-"UCL" positions in Denmark
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the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases”, led by Prof. Daniel Merkle. The expected starting date is 1 Januar 2026, with
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aspects of cheminformatics. The position is founded by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases ”, led by Prof
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600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This post is partly funded by
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SQUID magnetometry or similar techniques is a strong advantage. Experience in programming, ideally using Python to the extent that you can independently write programs to control and automate measurements
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. Required qualifications: A Ph.D. degree in Computer Science, Data Science, Software Engineering or related field. Solid research experience with using Large Language Models. Solid programming expertise in
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an independent and competitive research program, to contribute to teaching and supervision at all levels of education, and to collaborate broadly with the existing scientific staff. You will be offered local
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level and to be successful in attracting external funding. As an assistant professor in a tenure track position, you are expected to develop an independent and competitive research program, to contribute
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) Programming experience (e.g., Python, Julia) Strong analytical thinking and problem-solving abilities Interest in power and energy systems Excellent English communication skills and a collaborative mindset to
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experience in developing competitive national and international research applications Experience in programming languages (e.g. Python/R) and analytical skills in model evaluation Experience in advanced