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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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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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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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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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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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of (or aptitude to learn) quantitative data analysis and coding (e.g. R). Or a background in computer or data science who can demonstrate their ecological or natural history knowledge. Candidates should have a
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Models (LLMs). Orchestrating AI/ML pipelines in 6G. Developing certification and checking processes for code inside ORAN 6G. The research will be a combination of software engineering, radio
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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
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will bring to the role. You will need to apply for the PhD in Psychiatry, course code MDPS22, and name Dr Carrie Allison and Prof Simon Baron-Cohen as the supervisor. For the Statement of Purpose ¿ you
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state beyond a certain speed. Although predictions of sub-synchronous vibrations with current codes have shown good correlation with experiments under controlled lab conditions, this was only up to a