25 molecular-modeling-or-molecular-dynamic-simulation Postdoctoral positions at University of London in United Kingdom
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2025. We seek to recruit a Research Associate specialising in statistical modelling and machine learning to join our multi-university multi-disciplinary team developing a groundbreaking technique based
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About the Role We have an exciting opportunity for an individual to join our team, working in biomechanics. The successful candidate will create numerical models of biomechanical structures and
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About the Role The candidate will be working in the area of biomechanics. The researcher is expected to create numerical models of biomechanical structures and validate them through experimental
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and self-motivated postdoctoral researcher with a strong background in molecular and cellular biology, as well as computational biology. A track record of effective communication, teamwork and
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project investigating mechanosensing in Diptera. This post will focus on using detailed wing geometry models and kinematic measurements in computational fluid and structural dynamics simulations to recover
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of London. This Welcome Trust Funded post will be based at the Centre for Molecular Cell Biology (CMCB) within the School of Biological and Behavioural Sciences (SBBS) at Queen Mary. The project is focused
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About the Role This post is part of a dynamic collaboration between the Centre for Trauma Sciences and the Centre for Translational Bioinformatics. The Centre for Trauma Sciences, is a
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and/or evolutionary biology, with significant experience in embryological methods, single-cell/nuclei approaches, and general molecular biology techniques. A track record of high-quality published
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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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responsibilities will include: Pre-registering data analysis plans; Leading and conducting advanced statistical analyses (e.g., twin/family designs, genomic and epidemiological methods, longitudinal modelling