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-economic assessment and life cycle analysis methodologies. • Proficiency with modelling and simulation software relevant to TEA and LCA. • High analytical ability to analyse and illuminate data
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cannot see any personal data or the ‘Additional Information’ section in your application until shortlisting is completed. Shortlisting is by criteria-based questions based on the role specification, rather
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-economic analysis and life cycle assessment methodologies. • Proficiency with modelling and simulation software relevant to TEA and LCA. • High analytical ability to analyse and illuminate data
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their application clearly which they are familiar with and their degree of expertise). Experience of geo-coded data analyses and Propensity Score Matching would also be relevant. Expert interviews will also form part
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experiments and test candidate therapeutics on leukaemic stem cells isolated from primary patient samples. You will be responsible for carrying out laboratory research, data analysis and presentation of results
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the sector, yet a lack of gender-disaggregated data combined with the predominance of gender-blind programming means that workplace protections often miss key threats to women’s wellbeing. The research aims
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. The Research Associate/Fellow will be a human computer interaction (HCI) specialist in qualitative (interview) data collection, analysis, and sensemaking. They should also have a broad understanding of
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institutions, and leading industry partners. The successful candidate will contribute to the delivery of high-impact research projects involving AI algorithm evaluation and image data analysis. You will play a
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candidate will be responsible for the design, development, and execution of experiments, as well as data analysis and interpretation. This will involve using and adapting existing software, and developing new
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information about our work is available at https://www.nottingham.ac.uk/research/groups/low-carbon-energy-and-resources-technologies-research-group/research/microwave-processing/microwave-processing.aspx