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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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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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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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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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, analytical and computer programming skills. Advantage will be given to applicants with experience in one or more of the following: signal processing, deep learning, acoustics, psychoacoustics, acoustic
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | 24 days ago
, further exploring the carbon-related impact of polymer breakdown. The project will also incorporate artificial intelligence (AI) and machine learning to optimise degradation processes and data analysis
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treatment processes through advanced machine learning, validated against physics-based models and experimental data. 2. System Integration: Integrating the DTs into material and energy balance equations
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and problem-solving Qualifications Research Assistant post ● Nearing completion or working towards a PhD in Electronic Engineering, Machine Learning with a hardware focus or related area. Candidates
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untapped potential remains in extracting value from this data. This PhD will explore advanced analytics techniques, including machine learning, digital twin modelling, time series analysis, spectral analysis