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advanced analytical approaches, including deep learning and machine learning, to improve disease subtyping and risk prediction. You should have a strong willingness to learn, enjoy tackling challenging
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/augmented/extended (VR/AR/XR) environments to support learning of scientific concepts and practices at the university-level. The main aim of this work package is to investigate how such cutting-edge
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Other relevant professional activities Curious mind-set with a strong interest in enzyme structure and function An ability to learn new skills An ability to interact professionally with other scientists
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representation learning. Programming skills (e.g., Python) and experience with deep learning frameworks (e.g. PyTorch) Interest in applications to ecological or biological networks Good analytical and
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University. The project is a part of the ambitious Novo Nordisk Foundation Data Science Collaborative Programme, “Synthetic health data: ethical development and deployment via deep learning approaches (SE3D
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, with the earliest start date 1 November, 2026. Further details and application instructions are available at: https://math.au.dk/en/about/vacancies/phd The webpage includes brief subject descriptions and
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, ethnography, and policy studies. Further description of the project can be found here: https://dff.dk/en/our-funded-projects/meet-the-researchers/research-leaders/eksterne-personer-en/research-leaders-2026
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-Facilitated Blended Interaction Learning Spaces: Project framework A persistent challenge in higher education is the asymmetry between learning formats: lecture-based teaching offers students clear pathways
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Engineering, Machine Learning, Applied Mathematics, or a related field. A strong academic background and interest in AI systems, embedded intelligence, edge computing, machine learning, or related areas. Strong
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rapidly digitalising society and contributes to the development of sustainable, inclusive, and pluri-/multilingual ecosystems across Europe. More information may be found on the MultiLAwa home page https