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: 23.59 hours BST on Monday 25 August 2025 Interview Date: Wednesday 03 September 2025 Reference: PPS-0211-25 We are seeking a highly motivated Research Technician aiding the development of an organ
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Registered Veterinary Nurse to join the Neurology and Rehabilitation nursing team at The Queen Mother Hospital for Small Animals. This position is ideal for an RVN keen to develop their nursing career and
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their university experience. Our mission is “Together, we improve students’ lives,” and we work to build a stronger campus community, improve representation, and support student development. QMSU Services Ltd, our
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and assessing veterinary students in theatre related skills. This role offers an excellent opportunity to advance your clinical skills in addition to developing your teaching skills in a supportive
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influenceable non-pay expenditure and that procurement approaches are aligned to LSHTM’s mission, values and ambitions. You will be expected to further develop the procurement function, moving towards a category
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to develop business cases and drive resource efficiency. Excellent interpersonal and communication skills, with the authority to represent senior leadership confidently. A collaborative, inclusive, and
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. The Experiential Learning Manager will report to the Senior Manager, Experiential Learning and will be responsible for supporting the development and delivery of a range of London-based programmes, working closely
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this cohort are around 40,000 University of London students who study programmes which are developed and delivered in partnership with our 17 federation members. The University of London is also home to
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the College’s small animal referral hospital by further developing and delivering advanced cardiac surgical therapies through the open heart surgery programme, at the Royal Veterinary College. We are looking
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background in statistics or health research and an interest in building a career as a medical statistician. They should be enthusiastic, curious, and eager to develop an understanding of the statistical