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over India with Machine Learning’ (HEPPI-ML), which is funded through the ‘Weather and Climate Science for Service Partnership ’ (WCSSP) programme. It is also linked to the National Institute for Health
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multi-project collaborative research programme focused on how to improve quality and safety in healthcare. At assistant research professor level, the postholder will lead programmes of research, manage
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The purpose of this role is to support the work of the RICHeS programme at QUB providing research and access to archaeological and heritage science. The RICHeS Scientist (Research Fellow) will be a
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) section. The role involves working 50/50 across two projects: the NIHR funded Target Trials in Mental Health programme and Eli Lilly funded “Advancing the Methodologies Used to Incorporate Non-randomised
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Government policies and to inform innovation for industry leading to increased economic growth. Our main source of funding is from the Scottish Government funded Strategic Research Programme (SRP) which we
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obtaining, a PhD in computer science, engineering, mathematics, or a related physical sciences discipline, with research expertise in areas such as hardware-aware AI security, approximate computing, or secure
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the essential criteria for the post, which includes: Have or be about to obtain a PhD in computer science, engineering, mathematics or physical sciences area. Recent high quality research experience in
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The purpose of this role is to support the work of the RICHeS programme at QUB providing research and access to archaeological and heritage science. The RICHeS Scientist (Research Fellow) will be a
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an innovative research programme on decarbonisation within galleries, libraries, archives, and museums, with a focus on Scope 3 emissions. This Fellowship is made possible with support from Getty through its
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relevant field, including statistics, mathematics, computer science, epidemiology. Strong mathematical and quantitative skills. Experience in the implementation of mathematical or statistical models and