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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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designing and building visualization dashboards. Research experience in human-centered AI, or in the integration of AI and machine learning methods into interactive visualization and analysis systems. Strong
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at the interface between mechanics and machine learning? We are looking for a postdoctoral researcher for a fixed term, full time position at the Department of Materials and Production on Aalborg campus, starting 1
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intelligence and machine learning, with areas such as enzyme discovery and engineering, metabolic pathway design, genetic-code engineering, protein engineering, and the biosynthesis or biological incorporation
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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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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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) at the University of Southern Denmark invites applications for a postdoctoral research fellowship position within the field of neuro-morphic reinforcement learning to be filled earliest by 1 October 2026 for a period
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) invite applications from highly motivated researchers interested in an Industrial Postdoctoral position at the intersection of wireless communications, machine learning, embedded intelligence, and Internet
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span courses from bachelor to master level and will typically cover topics such as machine learning, deep learning, computer vision and programming. You will supervise student projects and theses at both
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statistics, AI and machine learning methods, including demonstrated experience in analysing multiple global change drivers, e.g. land use intensity, climate change, nitrogen deposition. Proven capability