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We have an exciting opportunity in the School of Mechanical, Aerospace and Civil Engineering to join the i4i-funded project ‘Step-sensor: Can sensor-based insoles detect changes in step quality
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candidates whose work lies at the intersection of statistics, machine learning, data analytics and modern AI algorithms. This includes, in particular, statistics for high-dimensional and complex data
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grant sponsored by the UK’s Engineering and Physical Sciences Research Council to develop a theory for novel bio-inspired micromachine sensors to measure acoustical quantities that have not been measured
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the cardiovascular system that are personalised to individual patients and updated whenever new data from wearable and implanted sensors are available. This post will focus on using these agile and personalised
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algorithms proficiency in both general-purpose programming (e.g., Python) and scientific computing, with a preference for experience in Julia Experience in writing up research work for publication Highly
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the University’s STEM annex in Markeaton Street, where staff offices and lab facilities are co-located. Key investments in the last few years include dedicated intelligent instrumentation and smart sensor
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for long-term production projects including large arrays of full-recticle and wafer-size semiconductor sensors, as well as one-off R&D pieces and small commercial activities requiring a rapid turnaround
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criteria Familiarity with the regulatory environment around Deep Learning or Machine Learning algorithms Experience applying quality system standards, software development standards and regulation, e.g. ISO
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, post-docs and interns collaborating across universities to build better algorithms, software tools and benchmarks to assess the safety of AI implementations at the software and hardware level. We
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. The task of the theory group led by Prof Kyriienko at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will