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The Medicines And Healthcare Products Regulatory Agency; | Canary Wharf, England | United Kingdom | 28 days ago
of CPRD's interventional research services. Responsibilities include defining the strategy and implementing standard methods and algorithmic approaches to data capture, transformation and export; undertaking
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King's College London Department of Engineering | London, England | United Kingdom | about 7 hours ago
methods. Depending on the strengths and interests of the PhD candidates, the PhD project will focus on some of the following aspects: The quantification of the fundamental physical and kinetic differences
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propellant space propulsion systems. A significant limiting factor of hybrid propulsion systems is the continuous change in surface area of the propellant grain during the combustion process. This changing O/F
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platforms, and/or those proposing to use quantitative/computational methods will be given preference. Applicants are also encouraged to think about the societal impact of their research, and for example
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, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform statistical analyses to assess stability and plasticity of multisensory
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Data Skills Advanced Quantitative methods Interdisciplinary Collaboration with researchers outside of the social sciences Please do speak to your selected institution should your project include any
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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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framework will be used with advanced causal inference methods – including inverse probability weighting to construct a valid comparison group. The analysis will use the potential outcomes approach to address
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annotations are scarce or unreliable. Recently developed unsupervised learning methods allow to circumvent this limitation by learning patterns in unlabelled medical images and then leveraging them
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, covering all cardiac conditions. This makes them unsuitable for identifying rare or complex cases, where annotations are scarce or unreliable. Recently developed unsupervised learning methods allow