60 parallel-computing-numerical-methods-"Simons-Foundation" positions at Lancaster University in United Kingdom
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parkland and beautiful seasonal landscaping. We have lots of facilities on-site such as: a sports centre, shops, cafes, a multi-faith centre, a post office, and a fantastic library. There are numerous clubs
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Lancaster UK, our network of five international study locations in China, Germany, Ghana, Indonesia and Malaysia, and numerous UK and global partnerships. You will work with colleagues at Lancaster UK
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to undertake assignments across project and/or service functions as required. You will work in close collaboration with the programme team and wider stakeholders, building effective working relationships at all
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of facilities on-site such as: a sports centre, shops, cafes, a multi-faith centre, a post office, and a fantastic library. There are numerous clubs, groups, and networks you can join to make friends with like
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will have experience of quantitative research methods and analyses. Knowledge and experience of statistical software packages is essential as is working as part of a multidisciplinary team is essential
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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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systematic methods, e.g. Garritty, et al, 2021). All reviews will include international literature and will scope beyond current knowledge of dementia and employment to understand the potential lessons
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across healthcare, academia, and industry. Explore the Medicine and Surgery programme Why work with us Lancaster University’s Bailrigg campus offers a vibrant work environment surrounded by green parkland
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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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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