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Field
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using advanced techniques like small-angle neutron scattering SANS and flow-induced polarized-light imaging (birefringence) Develop a novel experimental and simulation framework to explain, model, and
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your career in one of the world leading research institutions in Transport? Based in the Institute for Transport Studies at the University of Leeds, you will primarily contribute to the modelling and
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Stimulation, Computational Modelling, Biomedical Engineering and Biophysics, Neurosciences Admission requirements: Bachelor’s degree in Biomedical Engineering and Biophysics. Must have attended courses
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) position on the development and application of phase field methods for dynamic earthquake rupture simulations in the context of enhanced geothermal systems, CO2 sequestration, and earthquake physics
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develop and refine mathematical models of microbial interactions capable of predicting dynamics of engineered communities, and implement computational simulation, design, and inference frameworks
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training deep learning models on biological, chemical or related datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep
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of compound stability, release kinetics, and bioavailability using simulated feed manufacturing and digestive models. Undertake in vivo validation of delivery technologies in model organisms (e.g. Artemia) and
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: Essential criteria PhD in bioinformatics, computational biology, or a related discipline Extensive experience and expertise in applying/developing and training deep learning models on biological, chemical or
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function Apply machine learning methods to identify optimal model parameters that can be used in large-scale sea ice simulations (either global parameters, or as a function of existing model variables like
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highly skilled Postdoctoral Fellow with a proven dual‑mode research profile capable of independently performing laboratory experiments and coding predictive AI models in Python to forecast biomaterial