28 component-labeling-agorithm-cuda PhD positions at University of Nottingham in United Kingdom
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Soma Skins. The PhD will be part of the wider Somabotics programme that is exploring new kinds of creative interaction between humans and AI, especially robots. You will join a multidisciplinary team of
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. These analyses will be conducted using nationally representative databases; the Clinical Practice Research Datalink (CPRD) and Hospital Episodes Statistics (HES). The second part of the PhD project will involve
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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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interest in the linkage between the environment and fertility and the mechanisms involved. An underexplored element of male reproduction concerns the elasticity of the sperm cell membrane. Normal sperm
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/or dynamic analysis of mechanical/robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the-loop
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part of a much larger ERC funded project involving epidemiologists, historians and environmental scientists all seeking to understand the factors that have led to previous spreads of plague and the
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components. The project will deal with the micromechanics and in-depth materials analysis of advanced aerospace materials upon manufacturing operations to understand the materials' response
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. These analyses will be conducted using nationally representative databases; the Clinical Practice Research Datalink (CPRD) and Hospital Episodes Statistics (HES). The second part of the PhD project will involve
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field and an English qualification of 6.5 in IELTS (no less than 6.0 in each element). Other requirements are listed in the programme description. Deadline 1 April 2025 Funding
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strategies to critical subsystems or components, it is possible to achieve the same level of diagnostic accuracy and asset management effectiveness while significantly reducing the burden of data acquisition