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Job Description The Quantum and Nanophotonics Section at DTU Electro is seeking a highly motivated postdoc to be a part of a program on ‘Symmetry-guided discovery of topological photonics’, led by
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Researcher Development Programme targeted at career development for postdocs at AU. You can read more about it here . The application must be submitted via Aarhus University’s recruitment system, which can be
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at the candidate or master level, for example, Chemistry, Biology, Geology, Cognitive Science, Educational Psychology, Human-Computer Interaction, Education Sciences, or other relevant programmes that include
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these nanocomposites, we are looking for a postdoc to further develop high performance computing numerical methods in our state-of-the-art open source micromagnetic model, MagTense. MagTense is based on a core
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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
. Responsibilities and qualifications Your overall focus will be to establish and lead a strong research program in the field of synthetic biology and metabolic engineering of non-model microorganisms, with the aim
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at CSIC and UCM in Madrid, as well as Aarhus University, in a joint effort between the ERC Synergy project METRIQS and the Villum Young Investigator programme DynamiQ. Responsibilities and qualifications In
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postdocs. You will join a new research program on the role of universities and entrepreneurial ecosystems in building deep tech startups and scaleups. You will work towards building a landmark database on
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computational models to map co-expression networks and predict systemic disease transitions. Characterise intestinal microbiome changes and their correlation with inflammatory diseases. Computational modelling
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. Join us at the Department of Electrical and Computer Engineering, Aarhus University, where we are developing semantic-aware communication that leverage edge AI, semantic reasoning, and efficient time
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computational models to map co-expression networks and predict systemic disease transitions. Characterise intestinal microbiome changes and their correlation with inflammatory diseases. Computational modelling