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provides excellent access to research infrastructure, including databases, computational facilities and instrumentation, as well as to clinical materials and networks and training activities. The four
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technologies like normalizing flows, graph neural networks, and transformers to represent distributions over trees, to improve MSC estimation. These technologies have shown significant improvements in
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: Master’s degree in biomedicine or biostatistics. Doctor of medicine degree with clinical practice experience. Certified training in R and Python software. Documented experience using machine learning and
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program (Data-Driven Life Science) with focus on precision medicine. Access to top-level infrastructure, a new therapy development initiative for brain diseases (CNSx3), and a strong network spanning
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learning, deep learning and relevant software framework (R and Python) is highly desired. Very good oral and written communication skills in English are required. Emphasis will also be given on personal
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standard Python ML libraries (e.g., PyTorch) and software development tooling (git and docker) is preferable. Experience in the application of AI and Machine Learning in the analysis of scientific data