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, evaluation, and interpretation of AI models on single-cell biological datasets, while keeping downstream translation and valorization potential in clear focus. Key responsibilities Apply and evaluate advanced
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disease modelling skills to join our team. About the project The ultimate goal of this project is to develop and apply advanced human iPSC-based models to study complex genetic architecture
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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research institute with a unique collaborative model spanning nine research centers and four partner universities. Our mission is to advance life sciences for the benefit of society through scientific
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motivated and enthusiastic colleague with strong iPSC experience and disease modelling skills to join our team. About the project The ultimate goal of this project is to develop and apply advanced human iPSC
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multi‑omics data. You will also partner with AI experts to integrate predictive models and advanced analytics into omics workflows. You will work in an expanding team led by Dr. Masoomeh Rahimpour
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combination of infrastructure, scientific expertise, and collaborative model, the VIB Agro-Incubator functions as an international catalyst for advancing cutting edge agricultural biotechnology and is well
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colleagues on multi‑omics data integration and analysis. You will also work with AI experts to help implement predictive models that improve guide design and functional genomics workflows. You will join an
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. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
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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