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to deliver robust, scalable solutions that will eventually be integrated into widely used scientific software libraries. The successful candidate will join a dynamic research environment and gain access
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developed a unique methodology and software to simulate and analyse the performance of gas turbine engines in the past half century. The research in this area at Cranfield will be a good starting point for
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experimental test data. This project will harness new software capabilities to better understand bone mechanics, providing insight into the cause of OI fractures and its management. The successful candidate will
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focuses on the analysis of neuronal networks in the Drosophila brain, and the Hummel team currently consists of postdocs, pre-docs, master students and administrative colleagues who share a common interest
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of Text Analytics and head of the GATE team part of the NLP group at The University of Sheffield. She is a world-leading researcher in Natural Language Processing. She has been a leading developer of the
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discipline) Evidence of engagement in research activities (e.g., managing a research project, publishing journal articles, conference presentations) Experience of using statistical and/or analytical software
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mass spectrometry. Training on data analysis including relevant image analysis software, statistical analysis including graphpad prism and R and flow cytometry analysis using FlowJo will also be provided
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development Project-specific training and development opportunities may include tomographic tracking equipment used in experimental flumes and OrcaFlex and ANSYS/UFLEX software (or similar) for modelling cable
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consequence of the disease. Model results will be validated with experimental test data. This project will harness new software capabilities to better understand bone mechanics, providing insight into the cause
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PhD Studentship: Distributed and Lightweight Large Language Models for Aerial 6G Spectrum Management
: Algorithm Validation and Use Case Demonstration (Months 27–36): This WP will first develop an integrated hardware–software testbed to systematically validate the performance of proposed solutions under