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, they will take an active role in designing and commissioning a pioneering Self‑Driving Lab, a next‑generation autonomous research platform that will integrate Machine Learning and Bayesian optimization
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representations Analysis of structure–function relationships between morphology and movement Modelling genome–phenotype relationships using machine learning and genomic language models The project offers a unique
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intersection of machine learning and life sciences, developing next-generation models that improve our understanding of human biology and enable more proactive, personalized healthcare. As an Industrial PhD
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Are you interested in developing new image analysis and machine learning methods for cancer diagnostics and clinical decision support? Would you like to work in a multidisciplinary team together
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strategies. This project explores new methodological frameworks that use data-driven and learning-based techniques to enable intelligent, real-time decision-making in interconnected systems, such as in energy
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how we can learn from sensitive health data without compromising individual privacy. Using rich, nationwide Danish health registry data, the project focuses on spatial data, such as disease maps and
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trade unions, employers, and other relevant parties. Learn more about these initiatives at our Career Hub . The employment is in accordance with the Ministerial Order on the Appointment of Academic Staff
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analysis utilizing methods rooted in artificial intelligence (i.e. machine learning and deep learning). The analysis will be the basis for developing a predictive model to help select the most optimal method
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logistics, and it is considered an advantage if you also have knowledge of, experience in, or a strong interest in sustainability issues. You show initiative, have a strong willingness to learn, and are able
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–liquid interfaces through an integrated approach combining atomistic (DFT, AIMD, MD), and continuum (FEM) Modelling, supported by machine learning frameworks. Key responsibilities: • Perform DFT/AIMD