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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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Pytorch and/or JAX deep learning models. Experience in single-cell or spatial omics data analysis. What we offer Embedding within a computational team, with extensive experience in computational biology and
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mobility of migrants shape local populations? Developing a spatial microsimulation model of population dynamics with application in infectious disease modelling (DynaMIGs)”. DynaMIGs is a four-year
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will transition in a second phase to white box approaches that result in interpretable models. For ground truth data, μCT data will be used. A similar approach will be applied using surface roughness
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will employ advanced in vivo models and spatial technologies to dissect the roles of tissue-resident macrophages and infiltrating immune cells along the periphery–immune–brain axis. About us The research
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understanding on the origin of nucleic acids that are shed in liquid biopsies, such as blood, using cancer models (mouse and rat) and patient samples of neuroblastoma disease, a rare childhood cancer. Nucleic
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will employ advanced in vivo models and spatial technologies to dissect the roles of tissue-resident macrophages and infiltrating immune cells along the periphery–immune–brain axis. About us The research
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drive neuroinflammation in synucleinopathies and other neurodegenerative diseases. The candidate will employ advanced in vivo models and spatial technologies to dissect the roles of tissue-resident
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candidate will work closely with experts in food allergy, neuroimmunology, gut physiology, and computational biology to characterize immune cell responses, construct spatial maps of inflammation along the gut
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life. The successful candidate will work closely with experts in food allergy, neuroimmunology, gut physiology, and computational biology to characterize immune cell responses, construct spatial maps