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, with interests spanning a broad range of research areas - including methods for high-dimensional data and data integration, especially in molecular medicine; mathematical modelling of cancer
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
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Qualification requirements A master’s degree in a relevant discipline (e.g., statistics, mathematics, informatics, genetics, medicine, psychology, or an equivalent field). Strong expertise in statistical genetics
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informatics, mathematics, bioinformatics, computational biology, biology, immunology, medicine or a related field. Experience in bioinformatics and single cell technologies Experience in tissue handling and
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, neuroscience, educational sciences, or other AI-related fields, such as (neuro-)informatics, mathematics, or natural sciences, or must have submitted his/her doctoral thesis for assessment prior