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Programme: Hybrid CFD and process simulation for process intensification of post-combustion CO2 capture School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof
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that are conducive to successful completion of the problem at hand. Particular focus will be on multi-robot and multi-agent problems (e.g., navigation, cooperative transport, team-based agent games). The ideal
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similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural recordings Familiarity with neuroanatomy and neurophysiology Knowledge of dynamical
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neuroscience and data analysis Proficiency in programming (e.g., Python, MATLAB, and similar languages) Experience with large-scale neural network simulations Experience with analysing large-scale neural
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or social robots; trust and reliance on conversational agents designed to be charming and disarming; so-called "dark patterns" and manipulative tactics in the user interfaces of a range of technologies, from
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, working with legacy print, manuscript, and digital sources. You will apply and adapt digital methods (especially TEI XML), analyse provenance data, disambiguate historical agents, and contribute
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, disambiguate historical agents, and contribute to collaborative scholarly outputs. You will present your findings at conferences and help shape the project’s intellectual direction and future development. This
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how your experience meets the person profile requirements, a copy of your degree(s) certificate(s) along with a full transcript, and research publication list in the Upload section of the online
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Predictive Control (MPC) algorithms, innovative coalition-formation techniques, and validate these through high-fidelity simulations. You will design, implement and validate innovative data-driven economic
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experience in developing computational models and implementing models for computer simulations. Software development in C++ and/or Python is expected, and experience in model analysis and parameter