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performance and will guide the development of superior CO2 conversion photo/electro-catalysts. Candidates should submit a formal DPhil application (course code: RD_CY1A), following the links by clicking
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software development and highly proficient in computer programming languages for XR development. Proven ability to translate and implement specialised innovative ideas into functional code. Excellent
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purification is desirable but not necessary. Candidates with physics and physical chemistry are encouraged to apply. Knowledge of coding and image analysis is desirable but not necessary. As well as supporting
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code based on Modified Newtonian aerodynamics and a coupled, nonlinear thermo-structural finite element solver. Supervisors: Professor Matthew Santer, Dr. Paul Bruce. Learning opportunities: You will
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engineering or a relevant area. An MSc degree and/or experience and good knowledge in gas turbine theory, thermodynamics, Machine Learning, and computer programming will be an advantage. Funding Sponsored by
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Sciences, and Mathematics. Experimental experience in fluid dynamics and/or knowledge of any CFD codes would be an advantage, but not required as full training will be given. How to apply: Candidates should
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the 'Apply' button, above, quoting code MPB50490525. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up
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and manage independent research • Ability to set research goals, be self-motivated and proactive • A keen eye for visual presentation, software design, and in writing clear, concise, elegant code
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coding and CFD is advantageous but not mandatory—an eagerness to learn and innovate is key! Full training will be provided. Why This Matters Efficient storage technologies are essential for a carbon
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experience in computational modelling. It will involve the use of open-source computational fluid dynamics codes, with turbulence modelling and porous media approaches. It will also require the development