227 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" uni jobs at University of Oxford
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and advanced machine learning approaches to identify novel imaging markers of mental health disorders and cognitive function; 2) developing robust MRI-based acquisition, image reconstruction and
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The Department of Statistics is seeking to appoint a StatML CDT Administrator. The EPSRC CDT in Statistics and Machine Learning (StatML) is a four-year PhD/DPhil research programme. It trains
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service, has an appetite to learn, is keen to understand and support a wide range of technology and has outstanding written and verbal communication skills? We’re looking for an enthusiastic, customer
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computational statistics, machine learning, theoretical statistics, and probability as well as applied statistics fields, including statistical and population genetics, bioinformatics, econometrics, statistical
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wide range of libraries/frameworks and cloud infrastructure tools. Familiarity with Machine Learning, Neural Network and AI driven image analysis methods Experience with data management for large data
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of the U.S. You will be paid a stipend of £50,000 for the academic year. Most previous holders’ tenure have coincided with sabbatical leave from their home institution. The stipend is therefore intended
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productivity and output • Learn and be fully independent on the existing laboratory workflows, such as transcriptomics analytical pipelines running on Python such as Topometry • Manage own academic
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the Photonic Quantum Information group (PQI) led by Professor Ian Walmsley in the area of quantum machine learning. You will engage in advanced study and academic research, working to develop and carry out
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for the project’s goal and a willingness to learn and develop new skills as the work evolves. Given the highly interdisciplinary nature of the role, you will be expected to collaborate closely with researchers from
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5 years. The appointments will be in the area of statistical quantitative finance/financial econometrics, in particular data science and machine learning applied to quantitative finance