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combination of academic and industrial challenges which will enhance the student’s ability to tackle complex intellectual and practical aspects of computer vision and robotics. We are seeking talented
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details of the project informally, please contact: Prof Hywel Morgan, Digital Health and Biomedical Engineering Research Group, Email: hm@ecs.soton.ac.uk Entry Requirements A very good undergraduate degree
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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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candidates are invited to apply promptly as selections will be made on a rolling basis. Ideal candidates would have a strong background in Computer Sciences, Software Engineering, Artificial Intelligence
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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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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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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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, 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.