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publications Presentation skills Experience working with mouse models Knowledge of bioinformatics Downloading a copy of our Job Description Full details of the role and the skills, knowledge and experience
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in written and spoken English Structured and independent working style Desirable: Experience or interest in bioinformatics Wir bieten Ihnen Goal-oriented, individual training and development
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resources Minimum Education and/or Training: A Ph.D. in biomedical science, engineering, bioinformatics, or related areas is required. Backgrounds in cell and molecular biology, cell culture, imaging
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Cancer Center, as well as Genomics, Bioinformatics, and Organoid Shared Resources. Why work for the University? We have AMAZING benefits and offer exceptional amounts of holiday, vacation and sick leave
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, including bioinformatics, bacterial community profiling, microbial ecology, metagenomics, and multivariate statistics. They must also have experience working with arboviruses (e.g. viral culture, in vivo
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Bioinformatics expertise required for scRNAseq analysis. · Previous cell culture experience. · Perform molecular, cellular, biochemical and immunological analyses. · Optimize and troubleshoot experimental
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 4 days ago
to high-impact, translational research infrastructure at the intersection of biomedical informatics, cloud computing, and AI. Minimum Education and Experience Requirements Ph.D. in Bioinformatics
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A postdoc position in the Torben Heick Jensen lab, Aarhus University, Denmark: Mammalian Nuclear ...
to molecular biology and bioinformatics approaches. Collaboration with structural biologists is possible. Your profile Applicants should hold a PhD in Molecular Biology, Biochemistry, Cell Biology, Genomics
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Driver's License: A driver's license is not required for this position. More About This Job Required Qualifications: A PhD in Genetics, Bioinformatics, Computer Science, Data Science, Statistical Genomics
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bioinformatics methods have made significant strides, AI approaches - particularly deep learning - are revealing patterns and relationships in biological data that were previously inaccessible. As a postdoctoral