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support a high-value materials characterisation programme as a postdoctoral researcher. The ability to think outside the box with creativity, along with having the drive and ambition to develop those ideas
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or experimental methods, applied statistics, or computational social science. The position is open to candidates from relevant social science disciplines including political science, sociology, economics and public
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. In addition to the NIHR funded post available, locally funded posts may also be awarded in parallel, subject to funding and assessment against the stated criteria for the role. Applicants should be
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People and Finance Service Transformation (PFST) Programme Communications Officer Internal Applicants Only This is an exciting opportunity to contribute to a significant transformation programme
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software development in a team setting • Experience with version control distribution software like Git • Experience with numerical methods and techniques, including optimization and statistical analysis
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programme grant with partners across the UK to facilitate the use of hydrogen for aviation, and in particular the icing vulnerability of heat exchangers and parts of the airframe. You will work to generate
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contribute to a programme exploring how experimentation and innovation unfold in public services, using immersive qualitative research methods such as fieldwork, interviews, and facilitated learning sessions
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/workforce-and-learning-research-group ). The Compound Pressures project is a realist review funded by the NIHR HSDR programme. The project aims to understand how multiple and intersecting pressures, such as
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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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applications. Applications are sought from across a diverse set of disciplines under the Information Engineering umbrella, including, for example, physics-informed machine learning and AI, computer vision