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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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models and machine learning algorithms. These methods will be merged to support the derivation of an analytical equation for water table depth estimation. The ideal candidate will have experience in image
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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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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