21 senior-lecturer-distributed-computing Postdoctoral positions in computer-science in Denmark
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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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The Department of Computer Science at Aarhus University invites applications for a 24-month Postdoctoral Research Fellow in Explainable AI interested in interdisciplinary research between
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developing optimization-driven approaches to multimodal device tailoring. We are looking for someone with A PhD in Human-Computer Interaction or a closely related field Strong programming skills (e.g., Python
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to the organisation of academic conferences, as well as a range of outreach and knowledge dissemination activities, including the ABIS project teacher education program Department of Philosophy and History of Ideas
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you a Star Talent? Open postdoc positions at the Faculty of Medicine
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the opportunity to contribute to an internationally competitive research programme at the interface of proteomics technology development, regulatory protein biology, and cancer research. Expected start date and
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research career. Working at the Faculty of Medicine You will become part of a research environment comprising PhD students, postdoctoral researchers, and senior academic staff. This provides excellent
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research career. Working at the Faculty of Medicine You will become part of a research environment comprising PhD students, postdoctoral researchers, and senior academic staff. This provides excellent
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, and documentation of the WP5 experimental programme, including the controlled-environment and sterile cultivation set-up and the associated molecular and EV analyses. The postdoc will plan and schedule
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, extract, and standardise functional information 2. Develop computational tools that integrate evolutionary and functional information using comparative genomics and deep learning approaches 3. Apply