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successful candidate will work in collaboration with two other postdocs on a closely aligned project “Rethinking multi-agent systems in the era of LLMs”, funded by the Schmidt Sciences Foundation, and also
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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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velocities can reach relativistic values in the tail of the momentum distribution. Understanding how these relativistic electrons are transported through the plasma is a complex multi-scale problem
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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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we are committed to supporting the professional and career development of our postdocs and research staff. To help them thrive and achieve their ambitions, we have created a comprehensive range of
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projects, with a key focus on the recruitment of research participants. The post holder will also provide support to other members of the research group, including postdocs, research assistants, technicians
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for applications is 12:00 on Monday 7th July 2025. Interviews will be held as soon as possible thereafter. At the Dunn School we are committed to supporting the professional and career development of our postdocs
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leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis of normative frameworks and aggregation rules, and
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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