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IT and AV services that underpin technology-enhanced teaching, clinical simulation and hybrid learning environments. This is a pivotal role ensuring the reliable operation of technology-enabled
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into the sample of interest. Recently we have been using AI and machine learning to predict the distortion present and significantly speed up this correction process. This PhD project will take the latest in AI
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further developing new and innovative academic practice and learning opportunities working in collaboration with our partners across England. You will work as part of the course team supporting
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Computer Science, Artificial Intelligence, Software Engineering, or a related field. Strong programming proficiency in Python and/or C++. Demonstrable experience with machine learning frameworks (e.g., PyTorch
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reinforcing our Safer Recruitment commitment. We're very proud to be a signatory of the Armed Forces Covenant . an accredited Disability Confident Leader ; autism friendly university , committed to building
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, and community by reinforcing our Safer Recruitment commitment. We're very proud to be a signatory of the Armed Forces Covenant . an accredited Disability Confident Leader ; autism friendly university
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machine learning, Reliability Engineering & System Safety, Volume 264, Part A, December 2025, 111368 L. Deng, C. Shi, H. Li, M. Wan, F. Ren, Y. Hou, et al. Prediction of energy mass loss rate for biodiesel
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, and excellent learning and development opportunities. Informal Queries For an informal conversation about this role, please contact Dr Awinder Kaur, Head of Digital Technologies and Machine Intelligence
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feedback using machine learning and control engineering methods. The project will be hosted at the Bristol Robotics Laboratory (BRL), the UK’s largest academic centre for robotics research, with access
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, software engineering, Embedded Systems, Artificial Intelligence / Machine Learning, data science, or closely related disciplines or significant practical/industrial experience. Significant postdoctoral