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cases. This position is focused on advancing the capabilities of LLMs to address complex problems within specific scientific domains, with an emphasis on climate risk assessment and analysis. As part of a
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. Our research is rooted 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
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APPLICATION CLOSING DATE: April 13th, 2025 The integration of Artificial Intelligence, mathematical modelling, and advanced computational simulations of biological systems is transforming biomedical
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focus of the Inorganic Nanoparticles Group is the colloidal synthesis of advanced complex inorganic nanocrystals via wet-chemistry routes, enabling precise control over their composition, size, morphology
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; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; causal inference and time-to-event analysis; and statistical machine
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on developing machine-learning-based or statistical emulators to approximate key outputs of complex Earth System Models, with the aim of enabling efficient uncertainty quantification, sensitivity analysis, and
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We are pleased to announce a postdoctoral position focusing on developing advanced computational techniques to reduce the complexity in simulating lake physical dynamics at scale. Borrowing from
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studies effectively. They should excel in data analysis and quantification of results, paired with exceptional organizational skills to manage complex research projects. In addition to technical expertise
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report writing, with the ability to draw clear conclusions from complex data. strong numeracy and statistical analysis skills, with a background in mathematics and/or statistics. required skills: computer
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immunofluorescence. - Familiarity with toxicity assays and/or epithelial barrier function testing. - Competence in statistical analysis, data handling, and interpretation of complex biological datasets; experience