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the Computational Rare Disease Genomics (CRDG) Team, which is led by Associate Professor Nicky Whiffin and based within the University of Oxford’s Big Data Institute. The CRDG team collectively use
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inference attacks, to mitigate privacy leaks in MMFM. You will hold a PhD/DPhil (or be near completion) in a relevant discipline such as computer science, data science, statistics or mathematics; expertise in
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-certification, and redeployment, as well as social acceptability and policy design. About you You should hold a relevant PhD/DPhil, or be near completion, in electrical engineering, economics, applied mathematics
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
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Leedham (colorectal cancer biology), Dan Woodcock (cancer genomics), Helen Byrne (mathematical modelling), and Jens Rittscher (computational pathology and imaging AI), offering a unique opportunity to work
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Machine Learning, Human-Computing Interactions, Social Sciences, and Public Health. Applicants should hold, or be close to completion of, PhD/DPhil with research experience in computer science, statistics
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base, the partnership will bring together the University of Oxford’s expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will
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data from a variety of sources, including Spatial Transcriptomics and multiplex Spatial Proteomics platforms and developing skills in computational biology and mathematical spatial analysis via
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in Python, or demonstrated ability to rapidly acquire fluent knowledge of new programming languages, libraries, and platforms. A background and/or interest in mathematics or computer science would be
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projects. It is essential that you hold a PhD/DPhil in a quantitative or computer science related subject (e.g. Statistics, Machine Learning, Biostatistics, AI, Engineering), and have post-qualification