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microscopy data analysis, chemometrics, and machine learning. This position is ideal for a researcher who enjoys working at the interface of imaging, data science, and environmental monitoring. The project
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
Integration of phenotypic data with omics analysis Explore machine learning and network analysis methods Profile Essential A PhD in Bioinformatics, Computational Biology, Evolutionary Biology
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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in pre-processing and processing large biomedical datasets, including bulk and single-cell (epi)genomics and transcriptomics data using high-performance computing. You have excellent written and oral
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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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chromosomes, synthesize cell walls and membranes, and divide to give rise to daughter cells). Using a large-scale microscopy-based phenotyping approach that extracts high-content, quantitative information
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postdoctoral researcher - molecular mechanisms T-cell leukemia - Diagnostische Wetenschappen (28449)
Experience in bioinformatic analyses of large genomics data sets is preferred Experience in project writing and successful achievement of grants is a plus. WHAT WE CAN OFFER YOU We offer you a contract of
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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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sites using terrestrial laser scanning; (2) the development of next generation methods to enable big data science of forest point clouds; (3) the identification of key axes of variation of disturbed tree