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skills to work independently on a day-to-day basis. Applicants must have (or be about to obtain) a PhD in the physical sciences (or similar relevant experience); desirable fields of study include
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of probability distributions in systems driven by stochastic processes with Brownian motion. It plays a crucial role across a wide range of fields, from physics and biology to finance and engineering. But there's
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independent study and training courses. It is essential that you hold a PhD/DPhil (or close to completion) in mathematics, statistics, physics, engineering, data science or a related discipline, and have
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scientists, including software engineers and material scientists, from the Universities of Edinburgh, Stirling, and Arizona State University in the USA Your skills and attributes for success: The ideal
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About us The Faculty of Natural, Mathematical & Engineering Sciences (NMES) comprises the Departments of Chemistry, Informatics, Mathematics, Physics. The Department of Mathematics has a
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autonomy for mobile robots; Metric/topological robotic mapping and localisation for long-term operation; Learning for autonomous systems; Software engineering in robotics; and Integration and orchestration
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We are seeking a full time Postdoctoral Research Assistant in Safe Machine Learning for Power Systems to join the Foerester Lab for AI Research (FLAIR) at the Department of Engineering Science
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. Applicants should have a background in engineering, physics, micro-analytical systems, or microfabrication. Main Duties and Responsibilities Perform the following activities in conjunction with and under
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To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD awarded in Computer Science, Machine Learning, Biomedical Engineering
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(QMUL), is composed of academics, researchers, clinicians, data scientists and software engineers. The Group specialises in the advanced analyses of large electronic health care record databases, such as