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, you will engineer synthetic promoters controlling context-specific gene expression in Arabidopsis. You will develop high-throughput (molecular) phenotyping methods to screen transcriptional activity
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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
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their phytoplankton genetics expertise and learn our approaches in high-throughput metabolomics, enzyme assays, cellular metabolism, and metabolic engineering. We’re seeking someone independent, curious, and driven. As
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, CS, Bio-engineering, or Bioinformatics. You have experience with applying AI technologies in (regulatory) genomics, as demonstrated by peer-reviewed publications in international journals. Having good
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. Make sure that your application includes: A detailed CV A one-page summary of past research activities (e.g. in PhD/PostDoc projects) A one-page letter of intent describing your motivation
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of cellular metabolism or physiology. Experience in genetic engineering of phytoplankton or mass spectrometry-based metabolomics is a plus. The postdoc will get training in high-throughput metabolomics and
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that mimick human striatal function and we are using these systems to study the mechanisms of Parkinson’s disease. The system, that involves a high density multielectrode array enables us to measure single
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: https://cbd.sites.vib.be/en/technology Joris de Wit lab: https://dewitlab.sites.vib.be/en Anthony Holtmaat lab: https://neurocenter-unige.ch/research-groups/anthony-holtmaat/
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
with explainable AI (e.g., SHAP) Experience with high-performance computing and software containers Experience with software development tools (e.g., git, Nextflow) We offer The VIB-UGent
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Overview The group of Specialized Metabolism , led by Prof. Alain Goossens at the VIB-UGent Center for Plant Systems Biology, and the metabolic engineering research group, led by Prof. Marjan De Mey