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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
Job description We are seeking two highly motivated postdoctoral researchers to join our research team based in the Van de Peer lab, under the supervision of Prof. Dr. Zhen Li, Assistant Professor
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project Excellent communication skills in English Excited to help shape a super positive and social environment Key personal characteristics Independent and driven Enthusiasm to take on leadership and
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developmental biology, cell biology and evolutionary biology. We like to implement novel omics technologies such as single cell approaches and chemical biology to help us answering our biological questions
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. The names and contact details of 2-3 referees. For more information, please contact Dr. Sibylle Vonesch (sibylle.vonesch@kuleuven.be ) (only clarifications or further details regarding the vacancy
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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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will focus on the development, optimization and application of multi-modal analysis strategies and pipelines for sequencing data generated on nucleic acids isolated from biofluids (genomics, epigenomics
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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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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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and/or comparable expertise (e.g from industry). Demonstrated expertise in omics data analysis, for example with (meta)genomics, transcriptomics, proteomics, metabolomics, single cell and/or genotyping
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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