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for Translational Bioinformatics is a team of computational biologists, software engineers and data scientists located within the Digital Environment Research Institute (https://www.qmul.ac.uk/deri/) at Queen Mary
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treatments. To achieve this, we will develop personalised cardiac models at scale, and update these models over time, using imaging and electrical data collected by collaborators at multiple centres. We
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support projects using GWAS, Mendelian Randomisation, and polygenic risk score analysis to uncover genetic mechanisms underlying complex traits. There are opportunities to integrate omics data across
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including cell culture, organ-chip models, tissue engineering, and musculoskeletal biology. The PDRA will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and
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Dr Heli Hietala. The postdoc project involves primarily simulations informed by observations, related data analysis and theory/models, comparing various aspects of shock particle acceleration and meso
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to demonstrate effective and efficient multi-tasking and maintain accurate and up-to-date records. In addition, the applicants should have a high level of proficiency with computer software related to laboratory
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Right to work: Applications from job seekers who require sponsorship to work in the UK are welcome and will be considered alongside all other applications. For further information visit the UK Visas
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will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and help supervise associated PhD students. The successful candidates will join large, supportive
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characterise the internal dynamics of neural networks. Topological approach – based on metrics derived from topological data analysis to capture qualitative structural changes in the neural network configuration
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Right to work: Applications from job seekers who require sponsorship to work in the UK are welcome and will be considered alongside all other applications. For further information visit the UK Visas