52 computer-programmer-"IMPRS-ML"-"IMPRS-ML"-"IMPRS-ML" positions at Lancaster University
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, research and engagement. You will lead Lancaster’s contribution to dual degree programmes, maintain the highest standards of academic quality, and strengthen institutional profile and reputation across
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professionals and to play a key role in contributing to the University’s strategic objectives. By promoting Lancaster and the benefits of its study programmes, you will be helping future students picture
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the health economic component of the project. This includes designing the health economic plan which will involve workshops with key stakeholders to understand how sponsorship deals may impact on population
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for the development and day-to-day management of the system which will initially use face recognition technology. As such, the candidate will be expected to have excellent software engineering/computational skills as
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support, recent financial administration experience and have confidence using computer packages to complete tasks quickly and accurately within strict deadlines. You should also have excellent communication
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People and Organisational Effectiveness Location: Bailrigg, Lancaster, UK Salary: Senior Salary Closing Date: Monday 17 November 2025 Interview Date: Tuesday 20 January 2026 Reference: 0814-25 Lancaster University is a globally engaged institution set within a 578-acre parkland campus, home...
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data and Duolingo’s adaptive‑testing platform, ensuring that our methods are both sound and scalable. Lancaster University will provide dedicated high‑performance computing resources and expert
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of working in a similar environment. You should be comfortable working with computers and multiple software systems. You will need to be educated to GCSE level in Maths and English and be committed to high
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School of Computing and Communications Location: Bailrigg, Lancaster, UK Salary: £39,355 to £45,413 (Full time, indefinite with end date) Closing Date: Friday 22 August 2025 Interview Date: To be
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). The postholder will have a PhD in speech science, speech technology, linguistics, data science, computer science or related discipline. Ideally, they will have experience in working with large datasets of speech