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to study fundamental problems in biology and work towards foundation models of biological systems and innovative AI-driven biotech applications. The Laboratory of Computational Biology in Leuven
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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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-based models to study complex genetic architecture of neurodegenerative disorders. The candidate will approach this by: 1) using advanced Brain-on-Chip models to understand how genetic risk affects the
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mechanistic insight into the impact of WGDs on the evolution of molecular systems. In this project, we will use a mechanistic, sequence-based genotype-phenotype mapping model in combination with population
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hybrid models that combine deep learning with mechanistic models; foundation models of genome regulation using single-cell and spatial multi-omics data; AI-based modeling of biomolecule structures
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architectures for (bio)medical research and hybrid models that combine deep learning with mechanistic models; foundation models of genome regulation using single-cell and spatial multi-omics data; AI-based
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feedback. Hands‑on experience with biophysics‑guided modelling and force‑field‑based approaches (e.g. Rosetta, FoldX, or related methods), ideally in combination with ML models. Prior involvement in
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computational designs with experimental or wet‑lab validation and feedback. Hands‑on experience with biophysics‑guided modelling and force‑field‑based approaches (e.g. Rosetta, FoldX, or related methods), ideally
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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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‑electron tomography (cryo‑ET) to study in situ amyloid deposition and amyloid–cell interactions in experimental models and human tissues. This project is part of the BE.Amycon VIB Grand Challenges initiative