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labs framework. This studentship will include cohort-based training and activities, enabling students to gain wider skills and develop valuable personal and professional networks. Project Description
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remuneration package (including 39 days off a year and generous pension schemes). Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your
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is characterised by complex and highly dynamic turbulent flows that define the performance and design of renewable energy systems and their infrastructure. This PhD project aims to enhance
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on defining the initial separated fuel length scales. Fundamental to the definition of primary breakup correlations is the Weber number, which describes the ratio between air momentum and fuel surface tension
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including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during their PhD
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requirements. Build appropriate networks within the team. See full advert for full information. Education, qualifications and experience Essential MSc degree in a relevant discipline to the project: social
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, potentially including machine learning. This research will support the path to net zero flights and there will be opportunities to become involved in practical aspects of fuel system design and testing during
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, biologists, and engineers. You will also have the opportunity to present your research at international conferences, expanding your network and gaining valuable experience in scientific communication
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The Intelli-Ingest Doctoral Network is an EU-funded Marie Skłodowska-Curie Action (MSCA) initiative is a network bringing together leading academic, clinical, and industrial partners to train a new
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to improve structural durability, reduce material consumption, and support the UK’s net-zero goals. Funding notes: The position includes a full scholarship for UK-based PhD candidates and a half-scholarship