423 algorithm-development-"The-University-of-Edinburgh" PhD positions in United Kingdom
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laser diagnostics, analyse the results, prepare presentations, reports and papers, and interact with project partners. The skills, qualifications and experience required to perform the role are very good
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Description: This PhD project offers an exciting opportunity to co-develop and pilot a systems-based, interdisciplinary framework for circularity assessment in the water sector. Working closely with Anglian
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Cambridge, Cambridgeshire, UK. The key responsibilities and duties are to perform experiments with liquid-fuelled and hydrogen flames, employ laser diagnostics, analyse the results, prepare presentations
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political philosophy literature, drafting papers, developing and coordinating a seminar series, and overseeing the development of a journal special issue, and of a podcast on this cluster of topics. You will
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will combine 2 and 3D cell culture systems, gastruloids development, FACS drug screening and next-generation sequencing with investigation of patient samples, to identify and characterise targetable
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for cognitive and mood-related benefits and the interaction with the gut. The successful candidate will work closely with the supervisory team and key stakeholders at HTC Health to develop the specific programme
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of complex metagenomic data. You will also become proficient in lifecycle carbon accounting and data-driven decision-making, all mapped to the Researcher Development Framework at Cranfield University. Regular
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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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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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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