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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and
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. Funding This is a self-funded PhD. Find out more about fees. Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and
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flow visualisation and measurement techniques to study droplet impact under icing conditions to improve icing codes that aid in design and development of ice detection and mitigation system
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-informed data analytics tools for the predictive maintenance (PdM) strategy applications to high-value critical assets. Among others, the recently developed Physics-informed Neural Network (PINN) technique
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international research group at the forefront of the field Conduct a PhD within the frame of an innovative and interdisciplinary research project Interact with a wide network of peers, scientists and stakeholders
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directions will be pursued to enhance column generation using machine learning. The first line of research focuses on improving scalability by using Graph Neural Networks to identify and eliminate non
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PostDoc in the project). Collaborating with fellow researchers across the UPLIFT network, including those focused on digital twins at DTU Chemical Engineering- As a PhD candidate, your work will adapt
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Academies of Science Engineering and Medicine Workshops. Selected candidates will have the opportunity to train for publishing in leading biomedical journals and machine learning conferences, networking with
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a research assistant. Each candidate will also get the chance to build an international network and to engage with key scholars in this field, including the project’s Advisory Board. Qualifications
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sciences a pleasant and respectful working atmosphere integration into a successful and committed team in an international environment and network flexible and family-friendly working time models and the