106 algorithm-phd-"Prof"-"Washington-University-in-St"-"Prof" Postdoctoral positions at University of Oxford
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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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, 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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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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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in
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, “Determining extinction correlates on geological timescales”. Providing guidance to less experienced members of the research group, including research assistants, technicians, and PhD and project students
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screening (XChem), PDB deposition and biophysical techniques including SPR, DSF and NMR. Applicants must hold a PhD in Biochemistry/ Biophysics / Chemical Crystallography or a related field (or have submitted
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into disease progression, with the ultimate aim of identifying novel biomarkers and therapeutic targets. You will hold a relevant PhD/DPhil, together with sufficient specialist knowledge in normal and malignant
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of agentic behaviour and publishing high-impact research. Candidates should possess a PhD (or be near completion) in PhD in Computer Science, AI, Security, or a related field. You will have a Strong background
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full-time/part-time post is available from 13th October 2025 and is fixed term for 2 years in the first instance with the possibility to extend for a further 3. About you You will hold a PhD/DPhil (or
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via independent study and training courses. It is essential that you hold a PhD/DPhil (or close to completion) in mathematics, computational biology, physics or a related discipline, and have experience