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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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/directory/egegpdfib (via the 'Apply' button above) stating course code EGEGR3 with Project: Enabling a natural capital approach to infrastructure transitions with Dr Edoardo Borgomeo. The University actively
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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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provides a powerful, rapid and cost-effective model for testing the function of gene variants located in coding regions, generating results that can be validated in human cells. The student will employ
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or second-class honours degree in engineering, physics, mathematics, computer vision, or a related field. Interest or experience in computational modelling or coding—beneficial but not required. A
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computational elements, and some coding experience in a programming language (e.g., Python, MATLAB, Julia) are essential. The successful candidate will be supervised by: Dr Michael Short (https://www.surrey.ac.uk
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. How to Apply To apply, please complete the project proposal form linked to the specific project ensuring that you quote the project code reference and then complete the online application (linked
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into functional code. Excellent organisational skills, able to organise own research activities to high quality standards and deadlines. Strong self-motivation with ability to handle complex problems requiring
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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