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Engineering (PhD) Eligibility: UK Students Award value: Home fees and tax-free stipend £20,780 - See advert for details Project Title: Machine Learning and Optimisation-Based Intelligent Substation Design in
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A 3.5 year PhD Engineering studentship under the supervision of Dr Evgeny Petrov . Blade vibrations in compressor and turbine bladed disks are one of the critical issues in designing gas-turbine
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, biodegradation by the biofilm that develops on the granule surfaces plays an important role—sometimes enhancing, sometimes impairing the removal efficiency. Despite the importance of the combined effect
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epidemiology and machine learning. The scholarship will fund course fees up to the value of home fees*, a tax-free stipend of no less than £20,780 per annum), plus additional support for research expenses
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, machine learning, electrical engineering, or a related field. The ideal candidate will have some of the following skills such as: Computer vision and machine learning: A solid understanding of image and
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learning. Supervisor: Prof. Udo Bach, Department of Chemical and Biological Engineering. (Email: udo.bach@monash.edu ) Manipulating light at the nanoscale Supervisor: Dr Alison Funston, School of Chemistry
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
. •Specialist training in AI, machine learning, and digital engineering. •Collaboration with academic and industry experts for technical insight and mentoring. •A supportive research environment focused on both
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control software and machine learning expert. How you will support us: ▪ You will take on responsibilities in the field of control and operation of high-coherence superconducting quantum circuits, with a
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capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span a range of initiatives, including large-scale
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health monitoring, supporting studies in military aircraft systems. Engaging with these facilities allows students to acquire practical skills and technical expertise, enhancing their research capabilities