130 parallel-programming-"Multiple"-"Simons-Foundation" positions at University of London
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an extensive portfolio of in person, blended and online programme titles delivered from our campuses in London and Dubai and customized blended programmes delivered around the world. Programmes are targeted
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across multiple sites and provide the infrastructure and support for all our research, teaching and learning activities. About Queen Mary At Queen Mary University of London, we believe that a diversity of
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collaborations with external industry meet our ambitious goals for EDI across the sector. They will contribute to a range of Access Programme activities at the National Lab and Challenge Projects in the CDT
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activities, including updating course webpages, producing performance reports, managing social media content and scheduling, and supporting campaign delivery across multiple channels. You’ll also liaise with
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development of new partnerships, connecting into the CoSTAR Network and wider programme delivery. Lead and facilitate collaborative activities in support of enterprise and innovation goals, impact acceleration
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the strategic plan for the business unit, ensuring alignment with department goals and the School’s bold vision. Work hand-in-hand with internal teams, creative agencies, media agency and contractors — from first
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until February 2026. The Events Manager will work in partnership with stakeholders across the School, to plan and deliver high quality events that bring the London Business School brand to life and engage
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role requiring commercial expertise and the ability to convene and coordinate complex, multidisciplinary teams of internal and external stakeholders, whilst leading on multiple projects at different
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Experience with online learning platforms and performance tools. Strong communication, collaboration and influencing skills. Ability to manage multiple stakeholders and projects effectively. Experience
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education strategy across seven departments and multiple LSHTM-based centres, with a focus on building and strengthening skills in artificial intelligence and machine learning for epidemiological research