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, preferably in Python or R, and experience in the Linux environment Experience with large-scale data analysis, such as genomics or transcriptomics data Experience with a workflow management system such as
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medical development are welcome and we might actually recruit two persons with complementary expertise. Additional information may be found in the following selected references: De Strooper, B. & Karran, E
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intervention trials (e.g., diet, FMT), and ex vivo gut models enabling advanced multi-omics analyses of these samples. In addition the lab also maintains a large culture collection, partially linked to genomic
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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to integrate immunology, stem cell technology, and Parkinson’s biology. Supervise junior colleagues, contribute to grant writing, and disseminate findings through high-impact publications. Requirements PhD in
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for the design of synthetic promoters and data analysis. PhD in (Plant) Biotechnology, Molecular Biology, Biochemistry or equivalent A publication record in peer-reviewed journals, and excellent proficiency in
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computational and machine learning approaches, you will decipher genomic regulatory programs and infer the evolutionary patterns of gene regulatory networks in cortical neurons, study their developmental origin
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also opens new avenues for the design of climate-resilient crops. You will apply AI strategies to learn the regulatory syntax encoded by the Arabidopsis genome using single-cell transcript data as
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their impact on bladder function under physiological and pathological conditions. Work will include data acquisition, analysis, and interpretation, as well as collaboration with clinicians for human
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, industrial and medical applications and new innovative biotech companies. The Laboratory for Genome Editing and System Genetics at CfM combines development of high-throughput genome editing tools with large