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of computer science in proof assistants. Fluency in English is required. Questions? Curious to learn more about the position and environment? Please feel free to reach out to Professor and FORM Director Fabrizio
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. During employment, the assistant professor will complete the Lecturer Training Programme . Employment will be in accordance with the collective agreement between the Ministry of Finance and the Danish
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Postdoc position to support international research and capacity-building projects employing elect...
. Participation in fieldwork campaigns in Ethiopia multiple times per year (typically 2–3 weeks per trip), assisting with survey planning, deployment, and data collection. Contribution to the development
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Postdoctoral Position in Probabilistic Machine Learning for Spatio-Temporal Data Modelling A postdoctoral position is available at the Department of Computer Science, Aalborg University Copenhagen
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programs in Biology with about 400 students enrolled as well as a PhD program. The Department offers a vibrant and informal research environment with a long-standing tradition for collaboration with
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Are you interested in neuromorphic spintronic and can you contribute to the development of the project? Then the Department of Electrical and Computer Engineering invites you to apply for a one year
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determination methods (X-ray crystallography and single-particle cryo-EM) and a high-performance GPU computer cluster for structural biology. Your profile The successful candidate should have: A Ph.D. degree in a
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spanning protein kinase signaling, computational chemistry, bioinformatics, pharmacology, and molecular and cellular biology. The project aims to identify novel small-molecule, metabolite, or peptide-based
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. Contact information For further information, please contact: Assistant Professor Pablo Alcón, palcon@mbg.au.dk . Deadline Applications must be received no later than 18 December 2025. Application procedure
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biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and epigenetic mechanisms