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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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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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: Overcoming Inequity in Embodied Learning in Danish Vocational Education and Beyond, funded by Independent Research Fund Denmark. This is a full-time (37 hours per week), fixed-term (24 months) postdoctoral
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Are you analytically sharp and interested in how artificial intelligence can support learning and teaching? Then we have an exciting opportunity for you at Aarhus BSS. We are looking for a student
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Are you passionate about developing software for research projects? If so, the Software Engineering and Computing Systems section at the Department of Electrical and Computer Engineering at 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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the consequences of actions, and adapt reliably when the physical world changes? The project connects multimodal perception, reasoning and action with predictive learning and edge intelligence. Research directions
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aligned with the Science Team ‘Food Quality Perception and Society’ (FQS) at the Department of Food Science http://food.au.dk/en/foodresearch/science-teams/food-quality-perception-society/. The Science Team
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-in-research-and-development/software-engineering-computing-systems Further details about the Department of Electrical and Computer Engineering can be found here: https://ece.au.dk/en/about-the
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-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing