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will have a PhD (or close to completion) in engineering, materials science, physics or other closely-related disciplines. You will be a highly motivated and responsible researcher with strong curiosity
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attached to the project. The successful applicant must hold a PhD/DPhil in a relevant subject. They must have peer-reviewed publications using data science approaches, for example, genetic analysis
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responsibilities will include working within clinical researchers associated with the project, taking responsibility for completion of data analysis, and helping with the supervision of PhD students working
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across disciplinary and cultural boundaries. Completed doctoral/PhD studies in Physics, Theoretical Chemistry or Computer Science, or you expect to complete them in the near future. Established experience
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experience: Essential criteria PhD in computer science, AI or related area Proven experience of knowledge engineering and semantic technologies such as knowledge graphs, ontologies, data modelling, RDF, RDFS
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and leading a programme of numerical simulations relating to all aspects of our research on P-MoPAs; using particle-in-cell computer codes hosted on local and national high-performance computing
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term basis for 35 or 36 months from appointment. You will have a PhD (or about to obtain) in biochemistry, chemistry, cell signalling or related discipline. These roles are eligible for sponsorship under
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unique opportunity to work on a cutting-edge project involving multiomics data analysis of myeloma genomes, focusing on structural variants and heterochromatin rearrangements. You will have the chance to
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term basis for 35 or 36 months from appointment. You will have a PhD (or about to obtain) in biochemistry, chemistry, cell signalling or related discipline. These roles are eligible for sponsorship under
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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in