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real-world settings. This is an exciting opportunity for someone looking to develop their expertise in process evaluation, implementation science, mixed methods and applied health research, while
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of health or clinical data Demonstrable experience of applying statistical methods to complex research problems Proficiency in a range of statistical software (e.g. R, Stata, SAS, SPSS or equivalent
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Careers https://disc.hw.ac.uk/ . We welcome and will consider flexible working patterns e.g. part-time working and job share options. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total
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opportunities. We support staff wellbeing with flexible working options, work-life balance initiatives and support for physical and mental health. You can find more detail on all of this and more at https
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initiatives and support for physical and mental health. You can find more detail on all of this and more at https://www.qub.ac.uk/directorates/HumanResources/pay-reward-and-benefits Queen's University is
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year, pension schemes and development opportunities. We support staff wellbeing with flexible working options, work-life balance initiatives and support for physical and mental health. You can find more
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. We support staff wellbeing with flexible working options, work-life balance initiatives and support for physical and mental health. You can find more detail on all of this and more at https
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year, pension schemes and development opportunities. We support staff wellbeing with flexible working options, work-life balance initiatives and support for physical and mental health. You can find more
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good 2.1 Bachelors, or Masters degree in Electronic, Chemical Engineering, Applied Physics, Physical Sciences or equivalent. Experience in more than one of the following topics will be a plus: Working
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background in mechanical engineering, electrical engineering, mechatronics, automotive engineering, or physics. This is an opportunity to make a meaningful contribution to science by collaborating with leading