752 algorithm-development-"Multiple"-"Prof"-"Prof"-"Simons-Foundation"-"U" positions at University of Oxford
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that tackles global challenges - from advancing sustainability to pioneering healthcare solutions - and join a diverse, inclusive community that champions your wellbeing, development, and aspirations. Apply now
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into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
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We are inviting applications for an exciting new post for a Research Assistant to work with Dr Megan Kirk Chang on an interdisciplinary research program on the Oxford Health BRC Preventing Multiple
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for the technical development of the PRADA tool, an understanding of or experience with AI, digital apps and software algorithms would be desirable, as would an understanding of major depression and its
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, delivering tested methods, and creating algorithms to expand MMFM capabilities across domains like cardiology, geo-intelligence, and language communication. The postholder will help lead a project work package
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form, how it is generated and how it evolves. In particular we focus on the evolution and evolvability of vertebral counts, and we use various species of Lake Malawi cichlids as our model organism
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community that champions your wellbeing, development, and aspirations. Apply now to become part of our extraordinary legacy. What We Offer Working at the University of Oxford offers several exclusive benefits
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aims to develop formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research Assistant will support the development
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computational social choice, and aims to develop formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research Assistant will
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to advance hepatitis B and liver disease research and to develop novel analytic approaches for NHS routine data. You will be based at the University of Oxford, joining a collaborative, interdisciplinary