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Field
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aims at addressing computational challenges associated with data acquisition and information extraction from complex sensors and sensor networks. Crucially, uncertainty management and quantification
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from the Institute of Sensors and Signals (ISS) at Heriot-Watt University and Prof. Mike Davies at the University of Edinburgh, Leonardo staff, PhD students and the other PDRAs at the collaborating
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novel photonic techniques such as time resolved single photon technologies, spectral imaging, and optical fibre sensors to tackle clinical/biomedical challenges and other real world applications. Our work
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at the Blizard Institute to build and test custom made tendon-chips, using advanced bio fabrication techniques. You will join the Screen research group - a multidisciplinary team of scientists from engineering and
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. About the role To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD (awarded or thesis submitted) in Addiction Experience in
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systems with a particular emphasis on methods and systems that cope with imperfect knowledge and uncertain sensors. The research environment provides excellent opportunities for open-minded co-operation
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capable of driving the project forward. The ideal candidate: The ideal candidate will possess (or soon complete) a PhD in Theoretical Physics, Bio-Mathematics or Computational Biology. They will possess a
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system with integrated sensors. You should hold or be near completion of a PhD/DPhil with relevant experience in the field of robotics, biomedical engineering, information engineering, electrical
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We are seeking a highly motivated Research Associate to work on a Wellcome Trust–funded project using bio‑behavioural and data‑driven approaches to investigate emotion signalling mechanisms in both
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neurological function, including in rugby and snow sports. You should hold or be near completion of a PhD/DPhil in Biomedical, Electrical or Information Engineering or other relevant disciplines, and possess