47 optimization-nonlinear-functions PhD positions at University of Nottingham in United-States
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in a more accurate analysis of optimizing the service performance. Computer vision approaches such as ones for object identification and action recognition can help to automatically identify deviations
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functional performance of the components and the key process parameters. The project will deal with the design of special process setups, testing its working principles and performances followed by
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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Nottinghamshire NHS Foundation Trust. They will work as part of an established and diverse wider research team based at other recruitment sites in Sussex, London and Gateshead. You must have knowledge and
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Applications are invited to undertake a PhD programme, in partnership with Airbus, to address key challenges in ensuring adoption of sustainable approaches to fuel additives for aviation use
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highly efficient operation. TBCs are crucial to ensure the safe and high-performance operation of such critical parts under extreme temperatures and pressures; however, external contaminants (e.g. Calcium
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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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research area, and work alongside your peers for the first 10 weeks of your studies, splitting your time between high-level training and laboratory rotations. You will also take part in a three-month
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for Additive Manufacturing research group (CfAM). The student will work in world-class laboratory facilities in the CfAM engaging with interdisciplinary team with expertise in 3D printing, biotechnology, physics
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research group (CfAM) at the University of Nottingham. The student will work in world-class laboratory facilities in the CfAM engaging with interdisciplinary team with expertise in 3D printing, bio-printing