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with experience in one or more of the following areas: human genetics, computational neuroscience, multi-omics data analysis including RNA-Seq, and systems biology/network analysis. Strong data science
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, computer science, data science, or similar · Strong publication record in peer-reviewed conferences and/or journals · Experience applying machine learning methods (especially deep neural network approaches
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organised by the College of Medical, Veterinary and Life Sciences Graduate School. Full details of the programme are available at http://www.fom.gla.ac.uk/RDTC/ Regular attendance and contributions
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responsibilities will include: Establish and Lead Innovative Research: Develop a research programme addressing the Centre's strategic areas in cancer genome discovery, diagnostics, and translation. Foster
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individually, make a real difference. About the role The Department of Computer Science at the University of Surrey is seeking to recruit a full-time postdoctoral research fellow to work on a range of topics in
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. Alongside their research, Fellows engage in a series of leadership development activities, gain an in-depth understanding of the U.S. health care system and policy landscape, and build a robust network for
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innovative research culture in the Centre. The Research Fellow will use their research knowledge, skills and experience to contribute to the design and delivery of an ambitious research programme within
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responsibilities will include: Establish and Lead Innovative Research: Develop a research programme addressing CCGCM's strategic areas in cancer genome discovery, diagnostics, and translation. Foster Collaborations
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to evaluate and validate naïve pluripotency. Transcriptomics and network inference will be supported by computational/bioinformatics members of the team. Chimaera studies will be in partnership with our
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there is a premise for employment that the PhD Research Fellow is enrolled in USN’s PhD-program in Technology within three months of accession in the position. About the PhD-project Offshore wind energy