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dynamics simulations to recover dynamic strain and flow fields. Candidates should hold a PhD in a relevant biology or engineering discipline and be competent with numerical simulations. We are looking for a
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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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Pregnancy. Current risk-communication materials in maternity care are often text-heavy, numerically dense, and disconnected from the lived experiences of women and families. Building on prior epidemiological
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disease progression. About You Applicants should hold a PhD degree or equivalent in biological or related science and have a strong background in immune cell biology and animal models of inflammatory and/or
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and compare two distinct mathematical approaches to network metrology: Spectral analysis approach – based on network layer decomposition and spectral measures on singular values to mathematically
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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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dynamic strain and flow fields during flight. Candidates should hold a PhD in a relevant biology or engineering discipline and be competent with numerical simulations. Desirable competencies would include
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also have or be close to completing a PhD in any of the following areas as well as the will and commitment to learn relevant topics from the other areas: Statistical and machine learning, mathematical
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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