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In the framework of the interuniversity research project HOUDINI we are seeking a PhD student eager to contribute to the development and characterization of a humanized mouse model for Charcot-Marie
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biomolecular function? We are looking for an experienced postdoctoral researcher with a strong background in modelling of proteins and their interactions, including using empirical force fields, like FoldX. What
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work at the interface between neuroscience, modeling, and machine learning. You have good programming skills (ideally in Python). You are a team player with excellent communication skills. You can plan
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language models to decipher the genomic regulatory code, with a focus on the human brain. You will engineer new AI models to predict cell-type specific expression of all protein-coding genes in the genome
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Description The Yves Moreau and Stein Aerts research labs are looking for a shared PhD student to apply deep representation learning and large language models to decipher the genomic regulatory code
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., Vogels T.P., Greenberg D.S., Macke J.H. (2020) Training deep neural density estimators to identify mechanistic models of neural dynamics. eLife, 9, e56261. Lueckmann J.*, Gonçalves P.J.*, Bassetto G
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brain barrier models and/or experience with in vivo mouse experiments (Felasa C) will be considered advantageous. If you are passionate about pioneering research at the intersection of neuroinflammation
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explainable artificial intelligence), the goal of the project is to unravel the complex regulatory code controlling gene expression in the multicellular model plant Arabidopsis thaliana. Together with your
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the VIB–KU Leuven Center for Cancer Biology and the Department of Oncology. Our ambition is to develop representative models of human metastasis in vivo and in vitro and mechanistically tackle the site
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the preclinical test validation in murine cancer models, and clinical validation on human patient samples. You will coordinate the sampling of mice models and the collection of patient samples. You will co