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expertise/interest in Bayesian methods for addressing measurement error. Ideally PhD within the last 5 years. Advanced level experience with R, desired knowledge of Nimble, Overleaf. Excellent communication
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FAccT, KDD, SIGGRAPH, ACM Multimedia) Strong written and verbal communication skills in English Strong background in mathematical modelling and analysis Proficiency in software implementation
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seeking a postdoctoral candidate in the area of federated learning and wireless communications. The candidate must hold (or about to complete) a PhD in the related fields. The candidate will be involved in
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diploma in a biomedical field and/or in quantitative disciplines such as mathematics, computer science, data science, bioinformatics, or related areas. Completed PhD thesis in a biomedical field or in
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mathematics, or a related field. Experience in modelling community dynamics; prior work with size- or stage-structured models is preferred. Publication record commensurate with career stage. The working
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performance with classical methods. Qualifications PhD in Physics, Computer Science, Applied Mathematics, or related fields. Strong background in at least one of the following: machine learning, quantum
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kinetic models and their hydrodynamic limits. Dispersive phenomena in kinetic theory. Quantum gases. Applicants must hold a PhD degree in mathematics, physics or a related field. We seek candidates with
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presentations to stakeholders 3. Contribute to funder reporting Qualifications Must have a PhD or equivalent in applied mathematics, statistics, biophysics, or similar. Must be able to undertake full-time
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for 12 months and is available from 1st October 2026. The successful candidate will be based in the School of Mathematics and Statistics at the Open University campus in Milton Keynes. https
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Parks. The appointee may work on one or multiple additional ongoing lab projects, depending upon interests and past experience; opportunities also exist to collaborate with mathematical modelers, remote