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cases and controls); (ii) developing open-access databases and novel analysis pipelines (association study and machine learning) to characterize Campylobacter population structure and identify source
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We are seeking to appoint a Research Associate in AI with a specialism in Deep Learning. The Research Associate will engage in internationally leading research in the development of AI and machine
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development of common diseases. You will work on a collaborative project with Professor Ceclia Lindgen’s group at the Big Data Institute that aims to develop machine learning and laboratory-based approaches
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to 2 years in the first instance. You will be responsible for the design and testing of machine-learning based algorithms for HAIC. You will work with clinical domain experts to develop tools and
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and teaching. We are currently seeking a talented and highly motivated postdoctoral researcher in multi-omics and machine learning. The postholder will be a key collaborative link between the Nuffield
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understanding of the set-up and “muscle memory”. You will develop scalable and autonomous calibration frameworks to optimise quantum device performance. Machine-learning based algorithms will then make
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relevant PhD/DPhil (or near completion*) in Computer Vision or Machine Learning. You should have a strong publication record at the principal international computer vision and machine learning conferences
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, University of Oxford. This is a 36-month, fixed-term position, funded by the Simons Foundation. The start-date for this position is flexible, but September-November 2024 is preferred. The project will focus
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, machine learning, numerical analysis, optimization, scientific computing and their applications, to work within established research programmes. They will have excellent communication skills, including
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imaging data, using conventional analyses and machine learning, to provide new evidence of pathogenicity of proteins and pathways across MSK diseases. You will provide bespoke statistical analysis plans