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this testbed available to users for testing hardware and applications. NPL will lead on the testing and security evaluation of the testbed and collaborate widely on the technology development. The student’s
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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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co-supervised by both academic and industry experts, gaining valuable skills at the interface of hydrogeology, environmental engineering, and computational modeling. Research Objectives (1
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of environmental economics and innovation. The successful candidate will play an integral role in supporting data-driven, policy-relevant research examining the intersection of environmental challenges and
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the harmful effects of deepfakes on ordinary people. You will draw on methods from psychology, linguistics, data science, and computer science, such as behavioural analytics, neuroimaging, face and voice
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Solutions site, so applicants should be prepared to travel independently. Entry requirements Applicants should have a first or second class UK honours degree or equivalent in Chemistry or Chemical Engineering
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with Professors Serena Best and Ruth Cameron at the Cambridge Centre for Medical Materials in the Department of Materials Science and Metallurgy. The SHIELD Doctoral Network offers an exciting
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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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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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R&D (6.8% of turnover in 2022) and material science expertise make it an ideal industrial partner. Candidate Profile We welcome applicants with a strong academic background (first or upper second