19 machine-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions 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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of Prof. Georg Madsen, with regular shorter research stays at Aarhus University. The project combines density functional theory (DFT), machine-learned force fields and atomistic simulations to uncover how
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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position
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projects spanning data visualization, human-computer interaction, and human-centered AI. Coordinate scientific project activities, including planning, reporting, and coordination across collaborating
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Instagram? We are looking for a student to create authentic and engaging content for the Department of Computer Science’s Instagram channel, @csaudk. You will work closely with the department’s Communications
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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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an important challenge in Human-Computer Interaction research: how can we create a proxy for a remote physical object that does not replicate, but extends the experience of interacting with the object itself
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The Department of Electrical and Computer Engineering (ECE) at Aarhus University (AU) invites applications for a tenure-track position as Assistant Professor in Electronics. We seek a talented and
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for Statistical and computational Methods for Advanced Research to Transform biomedicine (SMARTbiomed) within the field of statistical and machine learning methods development for genetic analysis and causal