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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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analysis Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within an experimental team, with direct availability of experimental
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biomedicine and digital pathology Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within an experimental team, with direct availability
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experience with data analysis Enthusiastic team player Basic understanding of immunology Desirable but not required Experience in single-cell or spatial data analysis Machine learning experience Key personal
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-Molecule Drug Discovery Strong foundation in computational methods (e.g. docking, molecular dynamics, QSAR, machine learning) Experience working across diverse target classes Demonstrated impact on
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problems in biology by combining machine learning with in-depth knowledge of biological processes. Who we are looking for You have a Master in Science (Bioengineering, Biochemistry-Biotechnology, Biomedical
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onboarding period that includes specialized courses and hands-on training in AI and machine learning. You'll also have the chance to explore different labs and core facilities, meet fellow researchers, and
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scientific, societal and internal services that contribute to the reputation of the entire VIB and university. Your profile PhD or equivalent experience in machine learning or a related quantitative field
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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computational and machine learning approaches, you will decipher genomic regulatory programs and infer the evolutionary patterns of gene regulatory networks in cortical neurons, study their developmental origin