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to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device (SFDI) and also from our custom-built photoplethysmography (PPG) sensor
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We are seeking a research assistant with a background in computing to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device
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for clean energy technologies and develop the expertise that top employers and research institutes are seeking. The project is supervised by a strong interdisciplinary team: Dr Zakhar Kudrynskyi (advanced
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the perfect environment to carry out high-impact research that can genuinely shape the UK’s Net Zero future. This is your opportunity to create breakthrough materials for clean energy technologies and develop
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the University of Nottingham. This project aligns with Rolls-Royce’s technical needs to develop automated and hybrid tooling solutions for in-situ/on-wing repair and maintenance of gas turbine engines
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dynamic environments, including narrow spaces and interactions with unfamiliar objects. This project aligns with Rolls-Royce’s technical needs for developing soft robotic solutions to enable in-situ/on-wing
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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show
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dealing with investigations on the development of bespoke high-tech laser beam processing methods for surface treatment and repair of aero-engine components. The project will deal with the study of a new
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: Appropriate training within Rolls-Royce for a period to be agreed. The training will enable the understanding of the technical issues related to the project, as well as developing a good partnership with the
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Engineering Research Group) Aim: Develop a mathematical model for analysing reliability and efficiency of medical processes Background Adverse events and preventable failures in healthcare services represent a