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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 Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
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Description VIB.AI, the VIB Center for AI & Computational Biology, is a young research center dedicated to combining machine learning with in-depth knowledge of biological processes. Our mission is
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: 10.1101/2025.09.08.674950), and AI/machine learning. We work closely with clinicians to translate our findings into clinical practice, focusing on genomically complex sarcomas and haematological
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player and great collaborator Strong interest in interdisciplinary work at the interface between neurodegeneration, modeling, screening and machine learning Prior experience in iPSC modelling and CRISPR
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experimental workflows for generating and automating the acquisition of high-quality training datasets for machine learning models. Provide training to students on new technologies, protocols, and best practices
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the expertise unit into a dedicated team over time. Your profile PhD in machine learning, computer science, computational biology, statistics, or a related field. Demonstrated scientific excellence and leadership
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with large-scale data analysis, such as genomics or transcriptomics data Experience with a workflow management system such as Snakemake or Nextflow A willingness to learn and apply machine learning
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Data Core services, including high-performance computing pipelines and large-scale GPU resources, to scale LLM development and deployment. Your profile PhD in machine learning, computer science
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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