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points, inclusive – 3 points; Inferior or equal to 12 points – 1 point. Experience in: simulation and modelling, particularly using Ansys and OpenFOAM, phenomena related to fluid dynamics and heat transfer
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of the University of Southampton, but a large part of the research will take place in the community, and hybrid working is encouraged. The post is offered full-time or part-time, minimum 0.6 FTE, with a starting date
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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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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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: 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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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
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, FDM, and/or FVM will serve you well as you develop advanced numerical methodologies and software frameworks for the simulation of fluid-structure interactions of magnetoactive polymers, contributing
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Details Title Postdoctoral Fellow in Atmospheric Chemistry Modeling School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Environmental Science and Engineering
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of mathematical models and simulation of industrial Heat Exchanger to be used and deployed within the GEOFLEXHEAT project. This project, coordinated by Brunel, will support all the cross activities occurring during