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monitoring real-time social media conversations on antisemitism and synthesizing findings. Develop Python scripts and automated workflows to ingest, classify, and analyze data from our social listening
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should be detailed in the application form. Type of assistance may include monetary or in-kind contribution, skills mentorship, access to facilities, resources, development work or any other assistance
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industrial engagement. You will join the EPSRC project Towards Zero Carbon Aviation (TOZCA), a research project developing the tools, evidence and scenarios required to support the aviation sector’s transition
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multidisciplinary research programme focused on developing advanced AI-driven methods for neuroimaging, digital phenotyping, and population brain health. This programme brings together expertise in artificial
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industrial engagement. You will join the EPSRC project Towards Zero Carbon Aviation (TOZCA), a research project developing the tools, evidence and scenarios required to support the aviation sector’s transition
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Packages, developing partnerships with schools, project partners and other groups, and using mixed methods to collect and analyze new data and synthesize existing data sets. The four Work Packages focus on 1
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, combining synthesis of existing evidence with the generation of novel, regionally focused insights in order to support the Sheffield City Council public health team while they develop the scope for a new
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and Asia. This position offers an excellent opportunity to strengthen skills in primary data collection, advanced statistical analysis, evidence synthesis, proposal development, and scientific writing
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. The post will contribute to the development and evaluation of trustworthy AI approaches that support high-quality clinical documentation and safer decision-making in dental care. You will help deliver co
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holder will develop and implement mechanistic models to analyse and predict the behaviour of pharmaceutical processes. Your work will address key challenges within these processes, constructing robust