71 parallel-computing-numerical-methods-"Simons-Foundation" positions at Nottingham Trent University
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Neighbourhood Fund across five 'hyper' sites within Birmingham, Manchester, Norfolk, Cardiff and Bradford. This is a mixed methods evaluation and we are seeking someone with experience and skills in using
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capital theory and other relevant theories on sustainable development. Knowledge of these theories is not a pre-requisite to apply for this PhD. Method The project will employ a mixed-methods approach
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practices or outcomes. Methodology: The project can be conducted based on quantitative, qualitative, or mixed methods. We would welcome candidates who would like to explore the role of corporate governance in
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into multimodal transport. Yet these areas also face considerable challenges which mean that old models and methods may no longer prove useful in meeting the needs of communities in these areas. Further, the post
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in the UK. We pride ourselves on delivering high-quality teaching and diverse, real-world research. We specialise in biosciences, chemistry, computing and technology, as well as engineering, forensic
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to market insight, student recruitment, student experience and evidence-based course portfolio developments. You will support a broad research programme including competitor analysis, market intelligence
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are embraced and actively encouraged. The successful applicant will be part of the Creative Practices, Methods and Analysis CPMA research cluster. More PhD opportunities are listed on the CPMA website: https
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clearly and effectively using a variety of teaching methods. Previous experience in teaching at higher education level or significant industry experience is required along with a willingness to engage with
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of corporate governance in overseeing ML implementation Methodology The methodology for this project will be flexible and adaptable to the specific focus areas of the research. Several methods will be considered
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candidate will develop machine learning and algorithmic design skills. The candidate will gain valuable multidisciplinary skills in the area of machine learning and data analytics methods and their