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Applications are invited for a position in the rapidly expanding data analytics run by Prof Adam Dubis. The main focus of the team is to develop deep learning tools for prediction of disease progression
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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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stations, new and retrofit, leading to a substantial reduction in carbon emission to the atmosphere. This project will develop novel performance assessment tools for simulating the CO2 absorption process in
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modelling • A high fascination for technical/scientific problems of theoretical and numerical research • Experience in the field of numerical time-accurate flow simulation, preferably turbomachinery • Ability
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investigation of the aerodynamic performance of advanced future compressor stages, support-ed by numerical modelling and simulations of performance-enhancing design features. In this research project you will be
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disciplines). Experience in/Dedication to: planning and conducting chemical experiments, chemical analysis, process modeling/simulation, and optimization Team player skills and enthusiasm to work in a multi