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Field
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level. There is no plan to test any device in the stratosphere. Teaching/learning support, networking and planning the use of resources also takes up a small portion of this position. The skills
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plan to test any device in the stratosphere. Teaching/learning support, networking and planning the use of resources also takes up a small portion of this position. The skills, qualifications and
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teach at the University of Vienna, where more than 7,500 academics thrive on curiosity in continuous exploration and help us better understand our world. Does this sound like you? Then join our
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of the grade as required by the programme PIs The Person Knowledge, Skills and Experience Ability to work well as part of a team and rapidly acquire new skills Detailed subject knowledge relevant to cancer
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specific drug resistance and pathogenesis mutations. The project will combine classical microbial genomics with machine learning and AI analysis approaches to create the most in depth population analysis
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PhD Studentship: Sleep and Circadian Rhythms in Elite Sport (Co-funded by Brighton & Hove Albion FC)
in machine learning methods for pattern recognition and prediction. An academic or practical background in sleep science and/or elite sport is highly desirable. The candidate will be embedded within
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plus Familiarity with FE simulation tools such as ANSYS or Abaqus (or willingness to learn) General knowledge of structural analysis and material behaviour, especially failure mechanisms Some experience
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or Abaqus (or willingness to learn) General knowledge of structural analysis and material behaviour, especially failure mechanisms Some experience with coding, ideally in Python or MATLAB Funding support This
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central Manchester, the aim of this PhD project is to explore the impact of training musical performers from Global Majority backgrounds to teach children aged 6-16 from Global Majority backgrounds, and how
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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