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Bioinformatician

Oxford
University of Oxford
Posted: 22 October
Offer description

We are seeking

to appoint a Bioinformatician to join the Chinese Academy of Medical Sciences Oxford Institute (COI), an exciting collaboration between the University of Oxford and the Chinese Academy of Medical Sciences. This is a unique opportunity to work at the interface of translational systems immunology and cutting-edge multi-omic technologies, helping to uncover how the immune system responds to infection and cancer. You will be responsible for performing high-quality bioinformatic analyses of single-cell and multi-omic datasets, developing and optimising computational workflows, and maintaining robust pipelines for data management and reproducibility. You will collaborate with wet-lab scientists to design experiments, analyse sequencing data, and interpret complex datasets to uncover novel biological insights. A key part of the role will involve teaching and supporting COI researchers in bioinformatics methods, advising on data analysis strategies, and contributing to scientific manuscripts, presentations and grant applications. You will also help maintain and improve data-analysis standards, manage project timelines, and contribute to the overall research direction of the COI. It is essential you hold a postgraduate degree in Biostatistics, Mathematics, Computational Biology, Bioinformatics or a related discipline, with proven experience in functional or single-cell genomics. You should have strong analytical and quantitative skills, proficiency in programming languages such as R, Python and Unix, and a track record of delivering reproducible bioinformatic analyses leading to publications in peer-reviewed journals. Experience with molecular biology or genomics laboratory methods will be an advantage, as will familiarity with multi-omic integration approaches. You will be an excellent communicator, able to work effectively in a collaborative, interdisciplinary team, with strong organisational skills and a proactive, problem-solving approach.

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