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opportunities The student will join a team of postdocs, PhD students and technicians and will directly benefit from their hands on support and expertise. The student will use/learn cell culture, basic molecular
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) improve the estimation method using information from the first part of the work and additional constraints, including a Machine Learning approach. (3) inspect how the mismatched expected and measured
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, multi-disciplinary research group, and learn from experienced members of staff and other PhD students. Group members come from a diverse range of backgrounds and disciplines, with the group promoting a
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by the physical system. You should have a strong background in theoretical physics, mathematical optimization theory, or quantum error correction, and have completed or be in the final stages of a PhD
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explore data-driven methods including machine learning (ML) and artificial intelligence (AI) techniques, to develop predictive HMPM tools that can diagnose, detect, and predict faults in machinery
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Application Deadline: Applications accepted all year round Details Self-driving laboratories (SDLs) combine the power of artificial intelligence (AI) and machine learning (ML), robotics, and automation
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collected. The answer that excites scientists, engineers and clinicians today is AI and model learning strategies, coupled with privacy-preserving features. In this PhD you will tackle both halves
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. Criteria Essential or desirable Stage(s) assessed at A PhD in a relevant subject area or equivalent experience (e.g., operations management, operations research/management science, supply chain management
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apply. Criteria Essential or desirable Stage(s) assessed at PhD (submitted/awarded) or equivalent research experience in mechanical/chemical engineering Essential Application/interview Knowledge of Li-ion
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http://www.sheffield.ac.uk/sgs to learn more. Please apply for this project using this link: https://www.sheffield.ac.uk/postgraduate/phd/apply/applying Funding Notes First class or upper second 2(i) in