9 electrical-machine-"https:"-"https:"-"https:"-"https:" Postdoctoral 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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and different industrial outreach activities The candidate has at least the following qualifications - Applicants should hold a PhD in Computer Engineering, Computer Science, or similar - Cyber-physical
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data or large data volumes in all information systems. We contribute methods and algorithms for machine learning, and data mining, including XAI, as well as for data access and query processing. Aarhus
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others. Essential: Strong data analysis and machine learning skills and experience with PyTorch (or equivalent frameworks). Hands-on experience with data representation and embeddings, ideally applied
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these responses can be harnessed therapeutically. Current research integrates advanced immunophenotyping, systems immunology, single-cell multi-omics, viral genomics, and functional immune assays to dissect
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developing optimization-driven approaches to multimodal device tailoring. We are looking for someone with A PhD in Human-Computer Interaction or a closely related field Strong programming skills (e.g., Python
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to unlocking the full potential of nucleic acid–based therapeutics is their inefficient delivery to the cytosol. Current technologies like lipid nanopartcles (LNPs) are limited by poor biodistribution and