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participate in the development of a high-throughput data analysis pipeline and the development and testing of hypotheses. Key responsibilities Leading the development of mathematical models of post
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weekends to carry out cell culture and time-critical experiments, ensuring the continuity and integrity of long-term research projects. Evaluate scientific data from immunocytochemistry, flow cytometry, and
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project will compare the use of two different methods of catching and handling commercial poultry during loading for transport. The project will involve the collection of behavioural data and other measures
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communication skills, including the ability to write text that can be published, present data at conferences, and represent the research group at meetings. This full-time post is available immediately and is
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commercial awareness and business acumen. A collaborative team player, you will work effectively with both internal and external stakeholders to deliver tailored solutions. Further information on this role can
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highly desirable. Experience with green infrastructure, nature-based solutions, bioretention/rain gardens, or environmental data analysis will be an advantage. Enthusiasm for field research, the ability
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learning new systems and technologies. Further information on this role can be found in the job description. At Saïd Business School we believe in fostering a diverse and inclusive work environment where
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computational ecosystem, including shared codebases, data pipelines, computing resources, and public-facing research outputs (e.g. websites and repositories). They will collaborate across work packages and with
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, industry partners and central university teams, using data and insight to drive continuous improvement. Essential for success in the role: Proven leadership and management experience within FE and/or
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, stormwater/SuDS design, soil-plant-water interactions, or plant ecophysiology is highly desirable. Experience with green infrastructure, nature-based solutions, bioretention/rain gardens, or environmental data