364 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at University of Oxford
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well as companies and governmental organisations . They will contribute to the activities of the wider machine learning and data science research group and write up the results of their work, with co-authors
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computational statistics, statistical machine learning, simulation and statistical programming). The postholders will join the dynamic and collaborative Department of Statistics. The Department carries out world
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machine learning methods is desirable. Application Process You will be required to upload a covering letter/supporting statement, CV and the details of two referees as part of your online application
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initiative to find solutions to problems, or to progress key tasks. They will have an excellent standard of computer-literacy, and will have the ability to handle numerical data with confidence and accuracy
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the ability to learn new software packages and working knowledge of MS office including Word and Excel. Experience of change management and setting up new procedures and processes. What We Offer: As an employer
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). This role will primarily support the Professor of Clinical Machine Learning, Professor David Clifton, as well as other academic members of the group. The position is permanent and full-time, although
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collaborate with other technical groups working on the design. The successful candidate will also have opportunity to conduct experiments and machine development activities on the existing accelerators. The key
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leave schemes Cycle and electric car loan schemes Employee Assistance Programme Membership to a variety of social and sports clubs Discounted bus travel and Season Ticket travel loans How to apply: Please
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of the Department. The research activities of the department fall under eight broad headings, though there is much overlap in practice: Information Engineering (Robotics, Computer Vision and Machine Learning
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• A comprehensive range of childcare services • Family leave schemes • Cycle and electric car loan schemes • Employee Assistance Programme • Membership to a variety of