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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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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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: 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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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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following skills and experience: Essential criteria PhD in statistical/psychiatric/behavioural genetics or a related academic area with a strong data analysis component Excellent coding skills with a focus on
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academic area with a strong data analysis component Excellent coding skills with a focus on reproducibility and open-source publishing of code Experience of analysing large epigenetic or genetic datasets
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, biomedical engineering, psychology and have excellent coding and data analysis skills. You will be highly motivated, collaborative, interested in technology and interdisciplinary research and willing
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solid mechanics and fluid mechanics. Proven hands-on experience with code development for computational fluid dynamics or computational solid mechanics using the finite element method. Demonstrable