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candidate will have strong analytical skills and substantial experience in machine learning at scale. The Prorok Lab in the Dept. of Computer Science & Technology, has a variety of robotic platforms (aerial
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PhD Project: 3D-printing next-generation electro-actuators for soft robots and devices Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive
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focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data
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the solution of governing PDEs. - Train machine learning models to predict lifetime and failure based on loading and environmental histories. The PhD student will have access to world-class computing facilities
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together world-class expertise in textiles, materials, soft robotics, biomechanics, sports, healthcare, machine learning and AI, with globally leading industrial and academic partners. Your Project
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energy; thereby minimising farming’s environmental impact. AI machine learning offers a new expedient method of developing control systems for tasks that would be difficult to manage using classical
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
relevant field such as engineering, computer science, or applied mathematics. Experience or interest in AI, machine learning, or digital systems is beneficial. We welcome candidates from diverse backgrounds
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which there exists extensive experience in the areas of machine learning, biostatistics, and medicine: Dr Yanda Meng and Dr Tianjin Huang (Machine Learning), Prof Yalin Zheng (AI in Healthcare), A/Prof
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We are seeking a highly creative and motivated Postdoctoral Research Assistant/Associate to join the Machine Learning Group in the Department of Engineering, University of Cambridge, UK. This
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, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. Strong background/skills on machine learning, mathematics, probabilistic