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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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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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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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experiences and future goals a detailed CV including publication list contact information of 2-3 references The first review of applications will start immediately. A shortlist of applicants will be selected
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a postdoc, your career aspirations, your experiences in phytoplankton genetics, and a description of your previous research Your CV Contact information of at least 2 references Please submit
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Polleux, Nat. Rev. Neurosci. 2023). You will explore single-cell epigenomics and transcriptomics data, focused on the neurons of the cerebral cortex from human and an array of non-human species. Using
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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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the following documents: A motivation letter describing your previous research experience Your CV Contact information of at least 2 references For further information and questions, please email Joris de Wit
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Excellent communication skills in English Desirable but not required Skills in phytoplankton genetic engineering Hands-on experience with high resolution mass spectrometers and/or data analysis Programming