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evaluating computational methods, analysing imaging data, collaborating with clinicians for real-world impact, and contributing to publications. About You PhD (or near completion) in computer science
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. You will have demonstrable experience in the analysis of large-scale biological datasets, applying statistical modelling and computational approaches to high-dimensional data such as bulk and single
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About the Role This is an exciting position where applicants are invited to join a multi-disciplinary team of bioengineers, biomedical scientists, and computer scientists working together at Queen
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Arctica screening microscope with Falcon 4i detector and a 300 kV Krios microscope with K3 detector and an energy filter. We additionally have access to a large range of outstanding facilities
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and experimentation in the area of Multi-agent Agentic AI systems applied to 6G network and service management. By leveraging recent advances in Large Language Models (LLM) and other key agentic tools
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major hurdles in the use of genomic data in public health – access to big data sets, the technology to analyse these data, and the knowledge to interpret the results. In this role, you will develop
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motivated research assistant with a PhD degree and interest in bioinformatics or computational biology. The candidate will develop methods using liquid biopsy next generation sequencing data for cancer
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at the intersection of artificial intelligence, multi-omics integration, and cellular systems modelling. Based at the Big Data Institute (BDI) at the University of Oxford, the successful candidate will join the Ideker
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Clinical Cohorts Collaborative (PC3) which brings together multiple long-term UK Parkinson’s studies into a single large dataset comprised of control, prodromal and Parkinson’s participants. This post
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Clinical Cohorts Collaborative (PC3) which brings together multiple long-term UK Parkinson’s studies into a single large dataset comprised of control, prodromal and Parkinson’s participants. This post