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role in membrane remodeling. It also aims to deepen the mechanistic understanding of solute transport in ion channels and transporters of medical relevance. We apply state of the art methods
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, that combines diffusion and transformer models, there are clear indications that the analysis of this data can be automated. This will open new avenues in data interpretation and building predictive models
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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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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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motion) Pose tracking and behavior segmentation with tools like DeepLabCut, MoSeq, and Kinect-based systems Longitudinal analysis of behavior from early postnatal to adolescent stages in
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, qPCR, digital PCR, amongst others. Sequencing data analysis will be done using data analysis pipelines (Python, R) on the high-performance computing (HPC) infrastructure. About the TOBI lab
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will include data acquisition, analysis, and interpretation, as well as collaboration with clinicians for human tissue studies. The candidate holds a Master degree in biomedical sciences, medicine
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, molecular biology, or related disciplines FELASA certification Experience with or highly interested in experimental immunology (e.g. in vivo models, flow cytometry, imaging) Motivation to learn and apply
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prodromal cohorts and link them to clinical readouts and α-synuclein reactivity. Use cutting-edge single-cell and immune-profiling approaches, linked to clinical phenotyping, to discover early biomarkers and
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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