28 postdoc-distributed-algorithms Postdoctoral positions at University of Oxford in United Kingdom
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of Oxford. The post is funded by the National Institute for Health and Care Research (NIHR) and is fixed term for 24 months. The researcher will develop multi-sensor 3D reconstruction algorithms to fuse
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to reconstruct the tree-of-life on Earth, it allows us to reveal how biological function has evolved and is distributed on this tree, and it is the foundation that enables us to use model organisms
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at conferences, and represent the research group at meetings. You will be able to work in an effective, positive and respectful manner with other group members (DPhil students; postdocs) and collaborators. In
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postdocs and research staff. To help them thrive and achieve their ambitions, we have created a comprehensive range of opportunities and initiatives designed to provide an exceptional launchpad
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career development of our postdocs and research staff. To help them thrive and achieve their ambitions, we have created a comprehensive range of opportunities and initiatives designed to provide
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We invite applications for a full-time Postdoctoral Research Associate to join the new Data-Driven Algorithms for Data Acquisition (DataAcq) project. This is a timely project developing new
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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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of the research group, including postdocs, research assistants, technicians, PhD and project students, as well as to represent the PI and ISML when required. You will hold a Masters or PhD degree (or be close to
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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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settings. We are seeking a highly motivated postdoc to conduct research into this fast-moving area. Directions may include investigating quality evaluation methods for multi-agent systems, attack surfaces