105 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at Aarhus University in Denmark
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or similar. Experience in handling dynamic modelling and control, experimental setup and testing, Digital Twin and Machine Learning Publication experience Collaboration and/or management skills Communication
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dependable. You find enjoyment in working with data, learning new techniques, and applying them in rigorous ways. Ideally, you are at the end of your Bachelor, or start of your Master programme. In terms
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Applications are invited for a postdoctoral position in the group of Dr Aleksandr Gavrin ( https://mbg.au.dk/a-gavrin/ ) at the Department of Molecular Biology and Genetics, Aarhus University
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hosts several research groups in pure and applied mathematics and offers a dynamic and collegial academic atmosphere. More information about the department can be found at https://math.au.dk . Place of
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written and spoken Willingness to engage in interdisciplinary collaboration and fieldwork Advantageous: Knowledge of bat ecology and species identification Experience with machine learning or automated
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education in quantitative genetics and quantitative genomics (http://www.qgg.au.dk/en). QGG is an international organization with 70 employees and visiting researchers from more than 20 countries. We perform
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AACSB, AMBA and EQUIS accreditations. At the Department of Psychology and Behavioural Sciences, we teach and conduct research into the most significant subject areas of psychology. The department employs
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and reflects our values of respect, trust, recognition, and professionalism. Learn more about the Department here and the Faculty of Health here . Your job responsibilities Your primary tasks will be
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at two geographical locations in Aarhus and Roskilde. The Section for Biodiversity is situated in Aarhus and employs about 25 staff members. For more information on the Department see: http://ecos.au.dk/en
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be learned from these firms for innovation practice and theory. The research departs from the premise of the Danish Innovation Index: firm innovativeness can (and should) be assessed by those who