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Supervisors: Prof. Gabriele Sosso, Dr Lukasz Figiel, Prof. James Kermode Project Partner: AWE-NST This project utilises advancing machine learning techniques for simulating gas transport in
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quantification for greater accuracy and reliability. Material failure is a critical area of study in engineering, as understanding how materials behave under stress is essential for designing safe and reliable
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Supervisory Team: Prof. Gennaro Scarselli PhD Supervisor: Gennaro Scarselli Project description: Carbon fiber reinforced plastics (CFRPs) are popular in engineering applications due
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Introduction Health technology assessment (HTA) plays a critical role in ensuring that healthcare systems deliver value by informing decisions on the reimbursement and use of healthcare interventions
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PhD Candidate! Future synthetic cells will require an optimised gene expression system, capable of reliable, well-controlled expression of hundreds of genes on a synthetic genome. However, we cannot
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cooperation with Kopter Germany GmbH and the Engineering Risk Analysis Group of Prof. Straub, which provides information on both the health and the actual stress of helicopter components. For this so-called
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Medicine (Director: Prof. Dr. Daniel Rueckert) is seeking to fill PhD candidate position (TV-L E13, 100% for 3 years) in Privacy-Preserving and Reliable Artificial Intelligence to be occupied starting from