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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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-value reinforcements in their short and randomly aligned form. A key challenge to the effective reintegration of recycled carbon and glass fibres into high-performance products lies in achieving scalable
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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
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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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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 challenging properties of uncertainty, irregularity and
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Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM) at the University of Nottingham. The student will work in
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Applications are invited for a PhD project within the University of Nottingham’s Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM). The student will work in
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use this formalisation to encode our STV algorithm on encrypted ballots. This approach aims to ensure both the correctness and privacy of the tallying process, paving the way for verifiable and secure
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to the renewable energy revolution. Work with Industry Leaders: Collaborate with John Crane, a $1B global technology company driving innovation in sealing technologies. Gain Hands-On Research and Industry Experience