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code are encouraged as part of the application). Experience working with Unix-based operating systems, and tools for reproducible research (e.g. GitHub, Rmarkdown). Good communication skills and ability
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Analyse and interpret qualitative data using appropriate methods (e.g. thematic analysis) Use qualitative software (such as NVivo) to manage and code data Apply knowledge in a way that develops new
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, publications, conference presentations, code etc. Have a proposal which is within the AI in Science research remit. Fellows will join the Eric and Wendy Schmidt Network of researchers and will join a unique co
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their application clearly which they are familiar with and their degree of expertise). Experience of geo-coded data analyses and Propensity Score Matching would also be relevant. Expert interviews will also form part
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-based code optimisation. You will develop novel techniques that harness the power of machine learning to create optimisation strategies for compilers and memory management libraries for next-generation
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will have experience with zebrafish models, light stimulus design, hyperspectral imaging, and behavioural monitoring. You will be adept in coding and analysis using tools such as MATLAB and Python
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code are transparent, well-documented, reproducible, and openly shared with the scientific community. The role also offers opportunities to contribute to teaching and training activities across
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qualitative software (such as NVivo) to manage and code data Apply knowledge in a way that develops new understanding of dementia care delivery Support co-design activities with stakeholders in community-based
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projects. Have an outstanding research record commensurate with their level of experience as demonstrated, for example, through an outstanding thesis, publications, conference presentations, code etc. Have a
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presentations, code etc. Have a proposal which is within the AI in Science research remit and skills which fit the cohort of AI in Science fellows. Fellows will join the Eric and Wendy Schmidt Network