76 fully-funded-phd-program-computer-science-eth Postdoctoral positions at Aarhus University
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The Section for Electrical Energy Technology at the Department of Electrical and Computer Engineering (ECE), Aarhus University, is in a phase of rapid growth in both education and research
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Offer Starting Date 1 Sep 2026 Is the job 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
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Development Programme targeted at career development for postdocs at AU. You can read more about it here . At the Faculty of Natural Science at Aarhus University, we strive to support our scientific staff in
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Zheng. Your competences You have academic qualifications at PhD level, for example within computational biology, bioinformatics, spatial omics, or related areas. Experience with computational imaging
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of natural and synthetic catalytic RNA complexes focusing on circular RNAs and their potential role at the origins of life. COL is funded by the Villum Foundation. Expected start date and duration of
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with an interest in ecological applications. Required qualifications: PhD (or equivalent) in computer science, biology, software engineering, or a related field Strong proficiency in Python, including
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range from cell biological over biochemical to molecular biology and bioinformatics approaches. Collaborations with structural biologists are possible. Your profile Applicants should hold a PhD in
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, charitable trusts and foundations, international Universities and industry. The post holder will work as part of a recently-funded EPSRC Programme grant, undertaking research into nanotheranostics, support
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, neuroscience and personalised medicine. The Department of Biomedicine provides research-based teaching of the highest quality and is responsible for a large part of the medical degree programme. Academic staff
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qualifications include: Ph.D. in Computer Science, Computer Engineering, Electrical Engineering or a related field; Strong background in Deep Learning (e.g., Transformers, foundation models); Strong programming