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Field
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with a first class or upper second-class degree in engineering, physics, applied mathematics or a related field. A solid foundation in fluid dynamics and heat transfer, and experience with computer
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. Email: Xin.Dong@nottingham.ac.uk Due to the high volume of applications, we will only be contacting shortlisted candidates. Applications will be evaluated on a rolling basis until a suitable candidate is
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us to run large numerical simulations with billions grid points on mixed computer architectures including CPU and GPU machines. A current project is preparing the code set for the next generation of
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the foundation of computer vision, monitoring, and control solutions. However, real applications of AI have typically been demonstrated under highly controlled conditions. Battery assembly processes can be
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, with expertise in fluid mechanics and heat transfer Experience with OpenFOAM simulation software Programming skills with software such as Matlab and/or Python How to apply Please send an email with
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This project will include the payment of tuition fees as well as a stipend equivalent to RCUK rates To apply: send covering letter, CV and academic transcripts by email to Emma.Barney@nottingham.ac.uk
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Milisavljevic Syed Email: jelenams@cranfield.ac.uk If you are eligible to apply for this studentship, please complete the online application form.
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with engineering, physics, mathematics, acoustics, fluids, electronics or instrumentation background. Prior experience in computational modelling is beneficial, but not mandatory. Similarly, experience
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physiology etc. This PhD project is suitable for applicants with a background in Electrical and Electronic Engineering or closely related fields. Candidates with a strong interest in RF engineering and/or
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submit your application via the My Nottingham platform without having contacted our team first. Please contact the UTC Mechatronics Lead, Dr Abdelkhalick Mohammad, for further information. Email