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research combines inverse problems, numerical mathematics, optimisation, machine learning and imaging physics, with applications ranging from medical and industrial imaging to geophysics. For more
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cell biology, and enthusiasm for integrating clinical and laboratory data. Interest in machine learning, AI, and biomedical data integration. Experience with proteomics, genomics, and molecular biology
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, clinical data and AI-driven modelling for cancer research! In this role, you will bridge the gap between machine learning, computational biology, and haematological oncology. You do not need to arrive as an
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of the project thereby complementing the human data analyses performed in Maastricht. Post-translationally modified proteins (PTMs) and their antibodies have been long-implicated in the etiology of auto-immune