18 molecular-modeling-or-molecular-dynamic-simulation Postdoctoral positions at University of London
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project is to develop a series of surrogate models focusing notably on Physics-Informed Neural Networks to emulate the process of sediment deposition, diagenesis, and potentially fracturing, working closely
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), which houses the in vitro models centre alongside cell culture, biochemistry, microscopy and molecular biology labs. Details about the school and multidisciplinary bioengineering research activity can be
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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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, dynamic and growing discovery research group as a postdoctoral researcher. The postholder will work in Dr Knuepfer’s group, whose team explores molecular mechanisms of red blood cell invasion by malaria
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of inflammation on therapy resistance in colorectal cancer. Our lab is focused on understanding the cellular and molecular mechanisms promoting metastasis and therapy resistance in colorectal cancer. We use single
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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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offers an exciting opportunity for a talented cell and molecular biologist to gain experience in research in vascular biology with a focus on arterial medial calcification. This project, which is funded
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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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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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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