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systems. Analyse mixed-methods data (quantitative biometrics + qualitative focus groups). Collaborate with educators, engineers, and industry partners. How to apply To apply, please ensure you have digital
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with a new cutting-edge quantitative-trading company to push the frontiers of AI-aided decision-making in quantitative trading processes. As a PhD candidate you will: Design next-generation trading
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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your own learning at one of the world’s top 80 universities Take your career in exciting, rewarding directions Fibrosis is a scarring process characterised by the excessive deposition of connective
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supergiant stars right before the explosion Searching different astrophysical channels that produce r-process elements Connecting the properties of long-duration gamma-ray bursts and associated supernovae web
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exciting, rewarding directions The Opportunity: We are seeking expressions of interest talented candidates who wish to apply for a PhD to undertake research in digital health technology and implementation
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study flow dynamics relevant to reactor design using optical diagnosing methods, followed by image processing, which may include machine learning-based techniques. This suits Mechanical Engineering
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publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data
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- Ukraine conflicts, the Israel- Gaza conflicts, and Red sea attacks; Exploring the influence of digitalization in enhancing supply chain resilience, viability, sustainability, and adaptability; Analyzing
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, the aim of this project is to develop and validate an experimental paradigm that can describe the dynamic processes underlying C2 agility and to characterise the situational factors by which C2 agility can