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The School of Computer Science at the University of Nottingham is pleased to invite applications for a fully funded PhD studentship in deployable, efficient, and trustworthy computer vision. This is
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requires weekly travel to attend in-person training at these universities, which will be covered by the CDT. For further information about the CDT programme, please visit the CDT website at www.fusion
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support population-level prevention strategies. Further information: Applicants should have either a minimum 2.1 undergraduate degree in a relevant area (public health, epidemiology, economics, statistics
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support population-level prevention strategies. Further information: Applicants should have either a minimum 2.1 undergraduate degree in a relevant area (public health, epidemiology, economics, statistics
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-imaging modalities, such that molecular specific information can be obtained from microscopic biological samples and maps of cancer can be made. The probe will enable precise navigation into the body
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temperature interaction is not fully understood. This information is important as it can be used to inform new product formulations. Therefore, the aim of this Master of Research is to gain a fundamental
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to the interests of one of the School’s research groups: Cyber-physical Health and Assistive Robotics Technologies Computational Optimisation and Learning Lab Computer Vision Lab Cyber Security Functional
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mechanics. Skills you’ll gain Under the supervision of Charlie Heron and myself you will gain: Expert knowledge of centrifuge modelling challenges and solutions. Advanced programming/data analysis skills. How
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of experimental modelling challenges and solutions. Advanced programming/data analysis and simulation skills. How to effectively communicate complex and novel research. Opportunities to develop lab demonstration
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-edge adaptive mesh refinement techniques; a lightweight prediction tool developed upon the simulation data to predict key thermofluidic parameters for the design of high heat flux cooling components