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: 12 September 2025 Apply now Are you a data scientist interested in designing and implementing process-informed machine learning and uncertainties quantification methods? Join us as a postdoc and work
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programming (e.g., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication
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The Role Applications are invited for a three-year postdoctoral position within the Applied Mathematics research group, to start in July 2025. The position is funded by a UKRI/STFC grant to
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analysis of PDEs (with deterministic and/or stochastic methods), Gaussian Random Fields, mathematical foundations of deep learning, functional analysis and measure theory. You can find more information about
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theory, symmetry analysis, and group theory. You will work on developing and applying these ideas to discover new photonic phenomena, implement associated computational tooling, and to find opportunities
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Leedham (colorectal cancer biology), Dan Woodcock (cancer genomics), Helen Byrne (mathematical modelling), and Jens Rittscher (computational pathology and imaging AI), offering a unique opportunity to work
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nervous system. The successful applicant will work closely with industry sponsors who will help to guide the project. The Elbert lab and the industry partner are interested in developing mechanistic
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in basic research and centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus on ensuring that our
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combinatorics, Analysis of boolean functions Elon Lindenstrauss Homogeneous dynamics, ergodic theory, number theory, additive combinatorics Nathan Linial Combinatorics and theoretical computer science Cy Maor
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to the development of Ecological Risk Analysis Tables (ERATs) to support the development of coastal management accounting for climate change and species interactions. The post-doc will have an important role in