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partition functions; we will look to develop these connections further to obtain new counting algorithms. We will also investigate connections to correlation decay in the corresponding statistical physics
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Computer Science at Queen Mary University of London, working with Professor Rachel Humphris and Dr Dimitrios Kollias. The successful applicant will undertake computational research, including algorithmic
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will develop and apply computational methods for the analysis of cell-free DNA (cfDNA) sequencing data, supporting a growing research program at the intersection of epigenomics and translational medicine
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to trace how welfare algorithms operate in practice. They will also contribute to comparative analysis across case study countries, support interdisciplinary collaboration, engage with external stakeholders
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learning to improve detection using multiphase CT imaging and longitudinal biomarker data in routine practice. You will work with multidisciplinary clinical and AI teams on applied research, developing and
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in silico models to replicate disease. We are particularly interested in the effects of exercise on the development of bone lesions, and the potential role played by mechanosensitive osteocyte cells in
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applicants will lead a project focused on leveraging exciting newly developed experimental tools, including novel CRISPR-dCas9 epigenetic screens and cerebral organoid co-culture systems applied to patient
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About the role This role supports a multidisciplinary programme investigating the role of the Maresins, a family of pro-resolving lipid mediators, in early cancer development. You will process
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About the Role The principal duty of the post will be to undertake high-level lab-based work, developing the research program as outlined. The role includes data analysis and achieving a steady
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Trust-funded project on Plasma-Assisted Combustion (PAC) Modelling of Ammonia, in collaboration with the York Plasma Institute. The successful candidate will develop and apply advanced computational