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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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normally defined as within 3 months of application date). Desirable: Training in qualitative methods. Training or micro-credentials related to related to co-design community engagement methods, climate
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, qualitative evidence synthesis and some using more complex methods such as individual participant data or network meta-analyses. This is an exciting opportunity to be part of a new vision for evidence synthesis
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standard systematic reviews but might also include living reviews, qualitative evidence synthesis and some using more complex methods such as individual participant data or network meta-analyses. This is an
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Engineering, or related discipline, or equivalent industry experience. Practical experience of software design and development in a commercial R&D environment. Experience in producing high-quality outputs
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to microbiology and formulation science, specifically peptide handling, sterile formulation preparation, and physicochemical characterisation. Experience of using analytical tools and software relevant
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and Built Environment and to developing collaborative networks. A clear vision on future research and development plans and how they would benefit the School. Evidence for developing and maintaining
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building stakeholder networks and securing collaborative innovation funding7. Robust and resilient, with strong presence and the ability to confidently deliver complex messages to a diverse and demanding
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of research methods and techniques relevant to the FLF project. Ability to clearly communicate with a range of audiences and ability to build contacts and participate in internal and external networks
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appropriate languages and software, such as R, and of designing, developing or refining experimental methodologies to generate reliable and reproducible data. They must be able to analyse, critically evaluate