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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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fieldwork. It builds on the methods of anthropology and digital anthropology that emphasize direct observation of places, media, technologies, and practices. You will conduct ethnographic research in a field
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with quantitative methods (such as modelling and/or programming) to apply. PhD position: You have a master's degree in business administration, operations research, engineering sciences or similar
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methods (e.g., PCA, PLS-DA, clustering, neural networks) to enable automated, polymer-specific classification. Optimize workflows for high-throughput imaging and real-world sample variability, minimizing
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subteam, working closely with an experienced lab technician, two dedicated PhD students, and two postdoctoral researchers on a project focused on in vitro screening methods, including the use of organoids
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(applications by email will not be considered). Please include a single pdf in your application that combines the following elements: • a detailed CV (including publication list if applicable) • a one-page
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of CLiPS, which focuses on the application of statistical and machine learning methods, trained on corpus data, to explain human language acquisition and processing data, and to develop automatic text
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function of BLA neurons projecting to the PFC. You will use a combination of circuit tracing methods coupled with electrophysiology recordings and advanced transcriptomics and proteomics technologies
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generated on liquid biopsies with bulk/single-cell/spatial omics data generated on the tumors. You will benchmark methods with state-of-the-art approaches. You will be involved in setting up the wet-lab