84 algorithm-development-"Multiple"-"Prof"-"Prof"-"SUNY" positions at University of Leeds in United Kingdom
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are seeking a motivated Assistant Research Software Engineer who is eager to support world-class research through software development, data handling, high-performance computation, advocacy for reproducibility
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support of services that underpin a range of business critical activities and projects for our Digital Education Service as we undertake an 18 month change programme. This will focus on developing and
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venue. To realise this ambition, we seek to appoint a Business Development Manager who can proactively support the development, implementation and delivery of an ambitious sales strategy to grow and
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decision making, while you will be capable to apply machine learning and computational algorithms of social choice. This post is associated with following projects: Embedding EDI in the Distribution
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Multiple Sclerosis (MS) with a view to highlighting the implications for clinical practice. A recently completed PhD (PhD1) study, supervised by Dr Andrea Hollomotz and Professor Helen Ford at the University
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may include multiple finance workstreams including for example; Quote to Cash, Acquire to Retire, Transact to Record, Record to Report, Project to Result. Much of the work is expected to focus
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of working to tight deadlines and independently prioritising multiple tasks. This vacancy is within the Finance Service, based in the Faculty of Arts, Humanities and Cultures. However, should the business need
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effectively to meet deadlines, and you will be comfortable working across multiple project teams. Most importantly, you will be a people person who works best as part of a team and is committed to providing
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the climate crisis while also demonstrating a strong background in communicating evidence and insights to multiple stakeholders. Please note that this post may be suitable for sponsorship under the Skilled
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). This role is an exciting opportunity to take a role in the development, management and analysis of a new repository of Individual Participant Data (IPD) from ageing research trials. The work is an