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biomedical data scientist / computational biologist to join our highly collaborative team at QMUL. PhD (or close to completion) or research qualification/experience equivalent to PhD level in the relevant
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into clinically meaningful insights. About You We are looking for a motivated researcher with a PhD (or near completion in 2025/26) in statistical genomics, genetic epidemiology, bioinformatics, or a related field
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to work on a project investigating mechanosensing in flies (Diptera). This post will focus on using detailed wing geometry models and free flight kinematic measurements in computational fluid and structural
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About the Role We are recruiting an enthusiastic postdoctoral research associate to conduct a scientific programme of work focussed on pain mechanisms in epidermolysis bullosa, under the supervision
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qualification/experience equivalent to PhD level in a relevant subject area (physics, engineering, computing science, etc.). You will need as essential skills a good knowledge of C++ and python, familiarity with
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programme. The particular emphasis of the project will be to examine the interaction between atherosclerotic plaque macrophages and neutrophil extracellular traps and how it impacts cellular function and
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for medicine use before and during pregnancy. This postholder would work primarily on a recently funded programme of work to develop a novel approach to understanding and communicating the Safety of Medicines in
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About the Role The project “An Erlangen Programme for AI” (funded by the UKRI), will broadly involve applying advanced mathematical techniques for understanding training in neural networks, with
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help supervise associated PhD students. The successful candidates will join large, supportive research teams led by Profs Knight, Screen and Connelly all working collaboratively at Queen Mary. This is an
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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