182 developer-"https:"-"https:"-"https:"-"UCL"-"UCL"-"UCL" Postdoctoral positions in Denmark
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for a two-year postdoc, ideally starting August 1st, 2026. The position will encompass the ethnographic study of wind energy infrastructure development in Norway. The postdoc is part of the Sapere Aude
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collaboration with the project team take an active part in developing and fulfilling the different processes, meetings and events related to the project in close collaboration with the project team Qualifications
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Nordisk NERD grant, which will fund our research activities in quantum materials for the next 7 years. What we offer The successful candidate is offered: access to a well-developed research infrastructure
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) micro-CT imaging of breast cancer combining cutting-edge imaging technology with clinical pathology to develop quantitative 3D imaging biomarkers that bridge high-resolution micro-CT and histology. Our
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crystalline materials is often responsible for improved materials performance, but it is commonly overlooked in computational materials design. In this project, we will focus on developing accelerated
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Postdoc – Performance requirements for biobased construction materials used in the building envelope
existing materials as well as new products, covering both new buildings and renovation. Focusing on developing robust solutions that enhance the sustainability of construction, including increased use
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colleague to have strong skills in quantitative data analysis. The candidate should also be experienced in or willing to develop experience in subglacial and sediment processes, including an interest in
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approaches are transforming how next-generation biologics are discovered and engineered. We are launching an ambitious research program centered on AI-driven generative protein design to develop GPCR-targeting
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The Department of Business Development and Technology at Aarhus University invites applications for an 18‑month postdoctoral position in AI Ethics for the Public Sector, starting 1 September 2026
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imaging, deep proteomics, metabolomics, metaproteomics, and machine learning (ML) approaches to develop diagnostic classifiers, spatial tissue atlases, and identify potential therapeutic targets