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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
Method Development Develop novel genomic frameworks for detecting gene loss in plant genomes Implement approaches to distinguish DNA deletion from pseudogenization Analysis of gene
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analysis pipelines in a unique human brain circuit model to generate mechanistic insights, with the ultimate goal of combating Parkinson’s disease. You will have access to excellent support facilities
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spectral flow cytometry and microscopy (FELASA certificate required). Experience with -omic approaches and computational tools for data analysis is desirable. Solid publication record in peer-reviewed
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metastasis and novel metabolic pathways. We exploit mouse models, genetic engineering, metabolomics and single cell & spatial multi-omics analysis to gain groundbreaking insights into metabolism as a driving
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Post-doc eligibility criteria Required Skills Minimum 3 years hands on experience with complex flow cytometry is required, including panel design, testing, troubleshooting and analysis Experience in
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strong bioinformatics expertise and knowledge in programming languages and transcriptomic/multi-omic data analysis to help us unravel the complex interaction of cancer cells and their environments
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computing clusters and analysis of transcriptomics and genomics datasets. Desirable Requirements Experience in single-cell and spatial OMICS data analysis. Development of ShinyApps and
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analysis software, such as MZmine Programming skills in R Hands-on experience with untargeted high-resolution mass spectrometers Key personal characteristics Willingness to participate in interdisciplinary