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for one year, either full-time or part-time at 50% FTE The successful candidate will hold a Master’s or PhD degree in a Social Science or Science discipline demonstrating strong quantitative data analysis
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and child health. They will develop data analysis plans, organise data management, and conduct statistical analysis of national and local routine health datasets, including the Education and Child
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. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD in neuroscience/neuroimaging/neurobiology/ neuroinformatics/data
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of the research group, including postdocs, research assistants, technicians, PhD and project students, as well as to represent the PI and ISML when required. You will hold a Masters or PhD degree (or be close to
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stress resilience. Applicants must be highly motivated, with a PhD in plant biology or a related area. PhD students about to submit their thesis in a relevant area will be considered. The successful
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this post) a PhD in molecular biology, cell biology, pharmacology or a related area of biomedicine. Previous track record of high-quality research in the field radiation biology research or cardiovascular
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measurement in construction. The skills, qualifications and experience required to perform the role are: Hold (or be close to obtaining) a PhD in Computer Science, Civil Engineering, Data Science, Information
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of agentic behaviour and publishing high-impact research. Candidates should possess a PhD (or be near completion) in PhD in Computer Science, AI, Security, or a related field. You will have a Strong background
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arrangements. The post The Faculty wishes to recruit a Postdoctoral Research Fellow in Data Science and Data Engineering to support the work of Professor Gemma Sharp. This is a hybrid post based on the Exeter
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will plan and conduct experiments, generate high-quality data, prepare publications, make presentations and help supervise associated PhD students. The successful candidates will join large, supportive