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experimentation and training. Science of Deep Learning: Exploring mechanistic interpretability and understanding the fundamental drivers of model performance at scale. As an early member of this fast-growing team
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Development of reproducible software tools and computational workflows for biomedical research Develop novel AI, machine learning, and deep learning methods to address complex biomedical questions in diabetes
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BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and
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deep learning, with a sound understanding of experimental research methodology documented through coursework, projects, or publications. You must have strong programming skills in Python and experience
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visits abroad. This international exposure enriches perspectives and fosters cross-cultural learning, ultimately enhancing the quality of research outcomes. BIGS-LF does not offer PhD positions. You need
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cross-disciplinary and focussed on translating technological advances in biomedical engineering towards improving outcomes for cancer patients. PhD students within the group are supported by postdocs
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software or similar languages and experience with modern machine learning and deep learning frameworks parallel computing using clusters like UPPMAX and GPUs for high-performance computing and parallel
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postdocs in the SteeleLab in the Quantum Nanoscience Department in Delft. You will meet regularly with your supervisors and other team members, and also be encouraged to develop and explore your own ideas
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(preferably in Python, including deep learning frameworks such as PyTorch); affinity with medical image analysis and computational modeling; experience with neural networks for image analysis, generative
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 3 months ago
immunology with deep focus on T cells and Treg biology Hands-on experience with in vivo mouse models (FELASA certification is a strong plus) Practical experience in flow cytometry (FACS), including protocol