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research will develop and apply novel Bayesian machine learning methods – in particular physics-informed Gaussian processes and/or neural operators– to build accurate probability density functions (PDFs
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developed a wafer scale fabrication process for fabricating G-JJs across an entire wafer, up to 200mm with plans to scale up to 300mm. The SuperICQ consortium is a recently funded EU Pathfinder Open project
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Admissions Team that administers all stages of the high-stakes processes that recruit students to our Medicine programme. In addition, you will work closely with the Academic Lead for Widening Participation
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and climate adaptation worldwide. Your research will develop and apply novel Bayesian machine learning methods – in particular physics-informed Gaussian processes and/or neural operators– to build
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delivery. You will be a member of the faculty undergraduate administrative team of Undergraduate Programmes Coordinators, dealing with shared Teaching Office systems and processes for Biomedical and Life
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group and close partnership with Programme Leadership during the ongoing Curriculum Transformation Process. The post-holder is expected to demonstrate flexibility in teaching across an evolving portfolio
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-superannuable. For further details of the HoD reward or appointment processes, please contact Kay Bowen, Faculty Officer ([email protected]) Sabbatical HoDs are eligible, at the end of their period of
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to develop novel AI approaches for automated behavioural monitoring from underwater video, contributing across computer vision, machine learning, edge AI and interpretable decision-support systems
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Beijing Jiaotong University. You should focus primarily on delivering high-quality teaching across core Electronics & Communication Engineering areas, such as Digital Signal Processing,Advanced
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conversation ([email protected]) To apply for the role, please complete the on-line application process on Stonefish. The closing date for applications is 17th August 2026, interview date 28th August