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part of the Green Algorithms Initiative in the Department of Public Health and Primary Care, one of Europe's leading academic departments of population health sciences. The post will suit researchers
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the context of algorithmic problems related to constraint satisfaction and graph homomorphism and isomorphism problems. It brings to bear significant new mathematical (algebraic and topological) methods
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to translate biological processes into computational models. Contribute to algorithm development for large-scale simulations, especially parallelization. Create software solutions (such as games or demos
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animals, while Prof Durbin's works on computational genomics and large scale genome science, including the development of new algorithms and statistical methods to study genome evolution. Moving forward
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modern Bayesian modelling frameworks such as Stan, Turing.jl, and PyMC, including automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special attention will be
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in applying and developing the theory and algorithms needed to simulate these challenging systems is an essential prerequisite. The successful applicant must have a PhD degree in theoretical chemistry
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our software development team, developing novel scientific algorithms and applications in the areas of spectroscopic analysis and mining of the science data catalogues extracted from the pipelines
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. A typical candidate will have at least two years of experience in the following areas: advanced AI algorithms (e.g., generative AI, diffusion models), human touch sensing and tactile sensor
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An exciting opportunity has arisen for a talented researcher to join our team as part of the Green Algorithms Initiative in the Department of Public Health and Primary Care, one of Europe's leading
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organisational goals. Stay at the forefront of AI advancements, translating breakthroughs into actionable solutions. Develop robust algorithms and tools to analyse structured and unstructured data and improve