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with statistical or machine learning models, evaluation methodology, and messy real-world data, preferably within the biomedical medical domain A combination of academic and industry experience
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of integrative analysis of single-cell or spatial omics data, advanced imaging, AI/machine-learning approaches, mathematical modelling, or novel computational methods are especially welcome. The successful
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(SEM), multi-level modelling, Bayesian statistics, or approaches combining quantitative data analyses with machine learning. Documented experience in teaching and related activities, such as
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