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engagement through innovative digital solutions. Demonstrable ability to lead high-performing teams, foster collaboration, and drive a culture of innovation and inclusion, with an in-depth knowledge of digital
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Job Purpose To contribute to the activities of the Division of Small Animal Clinical Studies, School of Veterinary Medicine by delivering an effective and efficient high quality, small animal
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The successful candidate will have the following: Experience in the maintenance and operation of feeding equipment and working with dairy cattle Computer literate, with experience in using Microsoft Office suite
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to cutting-edge research on digitalised, low-inertia power networks. The role will focus on the development of open-source optimisation models for the GB electricity system with high levels of renewable
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local gas/liquid phase conditions. Whilst direct simulations of breakup are possible, computational cost is high, restricting applications to small sections of geometry and for modest run times
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required to have high performance, vacuum-based, insulation and integrate equipment capable of surviving this challenging environment. This adds weight and is one of the big challenges for aircraft
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-value reinforcements in their short and randomly aligned form. A key challenge to the effective reintegration of recycled carbon and glass fibres into high-performance products lies in achieving scalable
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these bioinformatic experiments. Access to a high-performance computer will be provided. The candidate must be capable of generating complex molecular compound models in silico and using current molecular dynamic
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flexibility is expected to work during high profile University events, such as Open Days, Graduation and Registration weekend. Physical requirements: This job involves walking, climbing stairs and the use
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, induct, train, coach, motivate and retain high performing staff, ensuring the team has the tools, competencies and commitment to deliver ambitious income and activity targets. Share best practice with all