362 algorithm-"Multiple"-"U"-"Simons-Foundation"-"Prof" "UNIS" positions at University of Cambridge in United Kingdom
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for the Future of Intelligence (CFI). The candidate will contribute to teaching and lead a research programme in one or more of the following areas: ethical use of machine learning, AI safety, algorithmic
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(Biochemistry, Neuroscience) MSc degree (or equivalent) in Epidemiology, Biostatistics, Data Science or related discipline. Strong quantitative analysis skills and experience developing algorithms and/or
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developments such as novel algorithms to support logistics operations, novel automation approaches or the design and development of new digital support tools for logistics providers. Significant flexibility
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A position exists for a Post Doctoral Research Associate in Department of Applied Mathematics and Theoretical Physics to work on the theory and implementation of algorithms and protocols on quantum
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experience managing, motivating, and developing service teams Can prioritise and deliver multiple areas of work efficiently and effectively Can lead and support teams through periods of change and process
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establishment or research facility. They will be organised and motivated to manage their own workload, with a proven record of meeting multiple deadlines. Educated to A Level standard (or equivalent) with
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wide range of student sponsors and Funding Councils, and the different working practices of multiple Doctoral Training Centres and Programmes. The Postgraduate Administrator is supported by the full-time
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to communicate clearly, manage multiple tasks, and work both independently and collaboratively will be essential to your success in this role. We are looking for someone with: Previous experience in administration
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contribute to the smooth running of one of the world's leading universities. The Role: Capture and accurately record customer service requests and updates in the CAFM system using multiple communication
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research group. The successful candidate will benefit from building upon novel datasets, exciting preliminary findings, and using unique experimental model systems. Techniques will include multiple imaging