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supported by the Cell-Scale Biomechanics Lab , and is part of the lab’s recent technology-development projects, aimed at improving the accuracy of drug efficacy screening for chemotherapy. A recent press
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reducing the environmental impacts of computational science. The tools and frameworks developed and maintained by the group are used internationally and include the popular Green Algorithms online calculator
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equations into AI-based models to solve fluid sensing problems in a robust and efficient manner. Your role may include developing new optimization techniques, coding new algorithms, creating new mathematical
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Location: South Kensington About the role: The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple
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acquisition of a range of environmental and operational data in the digitisation of food manufacturing processes for processing using applied AI techniques. We anticipate the successful applicant will develop
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our software development team, developing novel scientific algorithms and applications in the areas of spectroscopic analysis and mining of the science data catalogues extracted from the pipelines
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modern Bayesian modelling frameworks such as Stan, Turing.jl, and PyMC, including automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special attention will be
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dynamics and tissue morphogenesis during embryo development using cellular, molecular and mechanical approaches. Cell movements underlie tissue patterns and shapes. Using chick embryos as the model system
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/ production of relevant outputs (manuscripts, presentations, reports) relating to the ‘Social and Economic Predictors of Mental Disorders’ study (SEPMD), namely developing analyses and manuscripts to identify
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engaging outputs which explore what constitutes an end, who should decide and what should happen after. This is an exciting and varied role that involves developing and delivering the research objectives