26 modelling-and-simulation-of-combustion-postdoc PhD positions at University of Nottingham
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/or dynamic analysis of mechanical/robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the-loop
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| £20780 + £2500 industry top up (per annum (tax free)) Overview This exciting, fully-funded PhD opportunity invites applications from candidates with a robust foundation in data science, modelling, and
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application. Real-time simulation platform skills development including Typhoon and SpeedGoat. Development of real-time digital twin (physical or Artificial Intelligent based) of electric propulsion system
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modelling. This exciting project involves the application of innovative methods such as high-throughput experimentation to expediate the syntheses (and bioanalysis) of life-saving pharmaceuticals
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on modelling and testing of new reactors with a view to optimising the best systems for mixing supercritical water (>378o C and 221 bar) with wastewater feed streams. This needs to generate residence times
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gastruloids as a model system with which to study GAG structure/function relationships. Gastruloids are generated from induced pluripotent stem cells (iPSCs) and create in vitro models with which we can study
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Photovoltaic Modelling for Performance Optimisation Theme 3: AI-Enhanced Coordination of Renewable Energy for Smarter Grid Management Theme 4: Decoding Social Acceptance: The Community Lens on Large-Scale Solar
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will lead the development of novel motor topologies optimised for this cutting-edge material. Supported by experienced supervisors, the student will be able to design, model, and validate working
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network attractors, funded by The Leverhulme Trust. This is a brain inspired project in the field of Neurodynamics. Networks of oscillators are ideal candidates for modelling patterns of functional
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of deep learning models, especially when new training experiences are corrupted. The framework will be validated in robotic control scenarios during EV battery assembly, under process variations such as