320 modeling-and-simulation-"UNIVERSITY-OF-SOUTHAMPTON" Postdoctoral positions in United Kingdom
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organoid and across organoids, enhancing our theoretical understanding of the emerging information content within the single organoid and across the array, through the development of analytical and modelling
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. These include (1) encoding synthetic dimensions in molecules confined in rotationally magic traps and (2) the creation of many-body quantum states of molecules in optical lattices for quantum simulation (3
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expertise in organoid models of neurodevelopment to join our team and be involved in a MRC funded project aimed at generating region-specific brain organoids and assembloids from multiple gene-edited human
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://www.aria.org.uk/opportunity-spaces/nature-computes-better/scaling-compute/ The objective of our project, funded within this programme, is to develop a scalable and modular simulation framework. At the lowest level
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applicants for a 6-month paternity leave replacement who have a strong interest in using computational methods such as cognitive and psychophysiological modeling, (Bayesian) statistics and optimal experimental
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on Experimental Study and Computational Solids Mechanics model of soft multifunctional materials such as magneto-active polymers (MAPs), Electro-active polymers (EAPs). The successful candidate will work on the
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experts to acquire bespoke training and testing data; develop prototype solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated
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-reviewed journals, commensurate with stage of career Research skills or potential at an international level. Excellent track record of research in active matter or in the direct numerical simulations
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vitro, organoid co-culture models will be developed using primary human epithelial cells. Candidates should have an excellent research track record, be committed to the project and keen to work in a
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models