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challenge due to limited patient data—especially at the single-cell level—making traditional modelling approaches difficult. This project tackles that challenge by integrating multi-omics and clinical data
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. Knowledge of qualitative data acquisition and analysis and a keen interest in further developing your skills would also be an advantage. You will be a skilled and sensitive listener and communicator, able
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writing. Responsibilities will include: Conduct advanced multivariable statistical analyses of large-scale population-based data using SPSS Complex Samples and Mplus Draft and lead the submission process
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To work with Strathclyde Business School and National Manufacturing Institute Scotland (NMIS) colleagues to conduct research into digital transformation, develop case studies, support a large-scale
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30 PhD and post-doctoral fellows, and a large number of master’s students. About the PhD project: The goal of the project is to develop a simulation tool that, based on meterological and map data, can
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longitudinal aging study, the Betula Project, as well as the UK Biobank. The candidate will handle, process, and statistically analyze large amounts of data on blood markers, cognitive tests, and health and
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top-tier research team unlocking solutions to the scarcity of essential materials for next-generation energy and information technologies. You will use state-of-the-art computational tools based
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technologies into commercial products that solve big problems. We support research that universities, companies, and venture capital firms don’t fund because they view it as too risky. We prefer to use the word
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: Experience in physical system modelling including finite element modelling Experience working with large codebases in open source software environments Proficient user of HPC environments including MPI
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oncology grouping sees close to 550 new cases of these cancers a year. There is a large active clinical trials programme that spans phase 1 to phase 3. These patients have a poor prognosis, and this clinic