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Field
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for Resilient Water Systems Position Summary: We are seeking a highly motivated and interdisciplinary Doctoral Research Assistant to join a collaborative project aimed at advancing understanding of sediment
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advanced modelling, data analysis, and algorithmic development. Your tasks will support our core research focus of mathematical and computational approaches to design and implement solution algorithms, with
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), Paris, France. The candidate will be responsible for: - Modelling the health impacts of environmental prevention policies, particularly in the areas of air quality, noise, physical activity and/or urban
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with deep expertise in polymer synthesis, characterization, and structure–property relationships, and with a passion for pushing the boundaries of polymer research.Responsibilities - Conduct advanced
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Research Focus We are offering a Postdoctoral position in graph machine learning, algorithms, and graph management with particular focus on: Modeling real-world spatio-temporal energy networks Developing
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science, nonlinear optics, sensing, advanced imaging techniques and numerical modelling. About the role A successful candidate will join the EPSRC funded project “Catalysis meets plasmonics: New
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mitigate turbulence under diverse urban layouts and meteorological conditions. To achieve this, the project explores advanced machine learning approaches, including surrogate modeling and reinforcement
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. Advance Bayesian and ensemble learning approaches for non-stationary temporal processes. Implement probabilistic diffusion or generative models for long-term forecasting. Collaborate closely with
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. Familiarity with computational modeling of structure-function relationship Experience in identifying metabolites in biological samples. Sufficient knowledge in statistical analysis tools (e.g., SAS, R, XLstat
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include advanced and functional materials, chemical synthesis, energy storage and conversion, as well as molecular and materials modeling. Within this department, the Electrochemical Materials and