117 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Universidade de Coimbra" Postdoctoral research jobs at University of Oxford in United Kingdom
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application. In your supporting statement, please explain how you meet each of the selection criteria found in the job description, and why you would like to do this role. See guidance at https
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on “Active exploration of iridescence and gloss”. The ESR will join the EXPLORA consortium (https://explora-network.github.io/web/index.html), which comprises 12 academic institutions across multiple European
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fostering collaborations. You will lead the project's registered-reports and data-sharing strategy (OSF), prepare manuscripts and high-quality visualisations, and overseeing ethical approvals and participant
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About the role This fixed term, non-renewable, one-year postdoctoral position will support continuing analysis of data from the new London English Corpus, which has been developed as part of
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criteria found in the job description, and why you would like to do this role. See guidance at https://www.jobs.ox.ac.uk/cv-and-supporting-statement. Any technical questions related to this vacancy can be
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Academy of Engineering Green Future Fellowship, the postholder will design and integrate automated experimental workflows and data pipelines to accelerate the discovery and optimisation of OPV devices
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these and to deduce fluxes of heat and material across the MTZ. The post holders will be responsible for compiling seismic data sets (focusing on surface-wave overtones and body-wave data including precursors
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will include coordinating multiple aspects of the project, refining working hypotheses in light of new data, and contributing ideas for new research directions. The post-holder will be encouraged
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while contributing conceptually to the overall research programme. This will include coordinating multiple aspects of the project, refining working hypotheses in light of new data, and contributing ideas
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operando data related to battery degradation and safety. You will develop and implement advanced deep learning models to analyse multi-modal operando data from accelerated stress testing, with the aim