199 computer-science-intern-"https:"-"https:"-"FCiências" Postdoctoral research jobs in Denmark
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in research project management, and a relevant publication track record. Application deadline: March 20th, 2026 at 23.59 (CET) Place of work: Dept. of Computer Science, Aarhus University, Åbogade 34
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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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of circumstances under which university scientific advice is given to private companies; A background within scientific computing, using tools such as R, Julia or Python; Knowledge of using data science in relation
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of Mathematics and Computer Science offers an inclusive and international working environment with state-of-the-art facilities as well as a strong tradition for collaboration across departments and faculties, and
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of Molecular Biology and Genetics at Aarhus University seeking to understand RNAs role in the onset of Darwinian evolution. The lab takes inspiration from simple natural replicons for engineering RNA systems
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We are seeking applicants for postdoc positions in ‘Mammalian Nuclear RNA Production and Turnover Systems’ to join us at the Department of Molecular Biology and Genetics in the research team
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We are seeking applicants for postdoc positions in ‘Mammalian Nuclear RNA Production and Turnover Systems’ to join us at the Department of Molecular Biology and Genetics in the research team
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum
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next‑generation insect camera traps with on‑device (edge) computing for real‑time detection and classification Collaborating in an interdisciplinary team spanning ecology, computer science, engineering
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum