249 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" uni jobs in Denmark
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of publications (applicants applying for the position as associate professor should indicate scientific highlights), H-index and ORCID (see http://orcid.org/ ) Teaching portfolio including documentation
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international level, reflecting the academic age of the applicant; has experience in attracting and managing externally funded projects; can teach and advise students at all levels. Fluency in English is required
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developing the teaching program at the department. The candidate must hold a PhD in physics or equivalent and document the ability to teach physics at all levels of the University curriculum. The successful
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. They will develop new curricula and teach classroom-based as well as field-based courses and supervise students at all academic levels. Depending on research field, interest in collaborating with industrial
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scientific interests and priorities and they will establish a vibrant research group utilizing external funding. They will develop new curricula and teach classroom-based as well as field-based courses and
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Tenure-track Assistant and Associate Professorship positions in Algorithms at the Department of M...
interested in learning more about the position, please contact Head of the Algorithms Section Kim Skak Larsen at kslarsen@imada.sdu.dk. Conditions of employment Appointment as a Tenure Track Assistant
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testing and condition monitoring using modern machine learning, including multimodal foundation models and related data-driven and physics-informed approaches. Research topics may include visual and real
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on development of wave energy and offshore wind. Most of our research is focused around work in our wave flume and basin. Further description of the group may be found here: https://vbn.aau.dk/en/organisations
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school outreach activities. Teach in educational programs at the department, mainly within the pharmacy education. Participate in the daily operation, administration and further development
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Disentanglement of the Exceptional Biological Learning Machine, which is headed by Professor Jan Østergaard. The goal is to develop novel information-theoretic methods for identifying and analyzing temporal and