39 embedded-systems-"https:"-"https:"-"https:"-"https:"-"https:" research jobs at Aarhus University
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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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Role Description This is a full-time (37 hours/week) on-site role located at Åbogade 34, 8200 Aarhus N, Denmark for a Postdoctoral Fellow at the Department of Computer Science, Aarhus University
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is an advantage; a publication record that is competitive for the candidate’s career stage, along with the ability to present findings clearly through scientific writing and visualizations; and the
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social and intellectual organization of science reform communities. The expected starting date is October 1, 2026 or as soon as possible thereafter. The expected duration for the position is 2 years
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through the ODIN Grant program and is embedded in a broader initiative (AIMS) spanning clinical diagnostics, bioinformatics, and mass spectrometry methodology. It combines immediate clinical relevance with
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correlated structural disorder controls transport and other functional properties in energy materials. The position is available from the 1st of February 2027 or as soon as possible thereafter. Project
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on ocean and coastal dynamics, marine processes, and their response to environmental change through a combination of field observations, data analysis, and numerical modelling. The position is embedded
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The Department of Electrical and Computer Engineering at Aarhus University invites applications for a full-time, nine-month Research Assistant position in its Group of Integrated Photonics. Based in
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trapped ion quantum technology setups. The work will partly be carried out in the newly established Quantum Technology Lab (QTL) and within the Ion Trap Group. The position is open from the 1 December 2026
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are software representations of physical assets, processes, or systems. They leverage real-time data to mirror the behaviour and characteristics of their physical counterparts, enabling predictive maintenance