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Field
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conducting a survey, accessing and conducting the interviews with the Doctoral Training Centre alumni and other industry stakeholders, and performing the thematic coding and analysis of the interview data
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channels them back into new production processes, where possible. The case study region proposed for this is the West Midlands. The position requires an individual with a high-level of analytical capability
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to undertake independent research as well as working as part of a team. This will include using approaches or methodologies and techniques appropriate to the type of research, as follows: Write code to apply
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vulnerable to hardware-level threats, including side-channel attacks, fault injections, etc., particularly when optimized for performance. This Research Fellow position focuses on AI security in the context
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: Write code to apply biodiversity credit methodologies to data on a wide range of species groups. Co-develop, with the project investigators, scenarios for testing the methodologies. Develop and code data
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python code) in developing the UK MRIO for a range of applications, whilst working alongside the wider research team in an inter-disciplinary environment. You will display a strong commitment to applied
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outcomes through various channels such as conferences, seminars, and publications. Utilise acquired knowledge to foster new intellectual insights. Mentor students in research-related activities and offer
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tools, collaboration with project stakeholders, and engagement with the consortium and Defence and Security stakeholders. Technical Requirements: Strong coding skills with background in machine learning
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of foundation codes. Handling spatio-temporal statistics of forecast uncertainty will be a key consideration. This kind of downscaling with machine-learning methods is a rapidly advancing field and it is an
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degree and full GMC registration Rheumatology Specialty Certificate Examination (SCE) Proven competency in Python, R, and Stata coding Experience in systematic reviews and meta-analyses, including Bayesian