383 machine-learning-"https:" "https:" "https:" "https:" "https:" "University of St" positions at University of Oxford
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the leadership of Principal Investigator Dr Andrew Siemion. Listen's interdisciplinary research has synergies with many of the department's research priorities, including exoplanet studies, machine learning
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biology/bioinformatics, statistics, machine learning or related field. You will have a strong track record of applying genetics-based, physicochemistry-based and structure-based computational or statistical
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machine learning methods to model changes in the brain over the lifespan, including brain structure and function, and how those changes relate to environment and genomics. What We Offer As an employer, we
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We are seeking to appoint a Monitoring, Evaluation and Learning Lead within the Pandemic Sciences Institute. You will be responsible for providing expert leadership on monitoring, evaluation and
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Policy online course, which is FCDO’s flagship learning offer. The course aims to provide learners with a clear understanding of important economics concepts relating to foreign policy, development, and
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to work in the UK. The University of Oxford offers an attractive range of competitive benefits available to all staff for both work and personal life - https://hr.admin.ox.ac.uk/staff-benefits
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Skills Centre. The programme will cover all aspects of the role and will be delivered through in-house training, as well as block/day-release or other learning methods provided. You will complete a Level
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on “Active exploration of iridescence and gloss”. The ESR will join the EXPLORA consortium (https://explora-network.github.io/web/index.html ), which comprises 12 academic institutions across multiple European
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3.5-year D.Phil. studentship Supervisors: Prof Noa Zilberman The training of new AI models, as well as their deployment for inference, is transforming the design of computer networks. In
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the sequence of the human genome and the development of common diseases. You will work on a collaborative project that aims to develop Machine Learning and laboratory-based approaches, for decoding how the human