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interaction with materials, as well as surface reaction kinetics based on kMC-type descriptions. The main activities include: (1) the development of efficient surrogate models of kMC-based surface kinetics
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to wake development. Boundary conditions to the CFD model will be further developed to analyse the impact of meso-scale variation of the flow occurring over much larger spatial scales than the turbine array
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focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology
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in developing a continuous extraction process demonstrator to obtain extracts from microalgae biomass using pulse electric fields. The overall objective will be to propose an innovative method
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transfer This research combines advanced numerical simulation and artificial intelligence to develop predictive models for high-temperature multiphase flows, with specific relevance to steel casting
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to develop complement/augment classical CFD methods with quantum algorithms/techniques. The work lies at the intersection of multiphase flow physics, numerical modeling, and quantum computing. Who we
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parameters, optimising these and various process conditions to enhance the overall performance of the gas turbine employing specific indicators. Used with a complementary CFD modelling approach, the research
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develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel solver, capable of running
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support for process development from laboratory to pilot to demonstration scale Working with a wide range of simulation tools such as CFD, numerial optimisation and artificial intelligence Topic-independent
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collaborators. Under this job title, you will develop a CFD modelling platform to evaluate the combustion, flammable and toxic gases emission and dispersion characteristics resulted from battery fires/thermal