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for an enthusiastic and highly motivated Research Associate or Research Assistant in Medical Statistics to join an interdisciplinary team focused on improving lives through world-class research in ageing, sarcopenia
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Associate in statistics to the 3-year Engineering & Physical Sciences Research Council funded project PINCODE: Pooling INference and Combining Distributions Exactly: A Bayesian Approach. The Bayesian fusion
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analysis (e.g. economics, statistics, mathematical modelling). They will also have completed an MSc in one of these areas. For the position of Research Assistant, applicants should have a Masters in Health
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thesis for examination. You will have experience with data handling, databasing and statistical/bioinformatic analysis as applied to translational cancer research, and a keen interest to develop your
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independent signal processing, statistical and computational skills, and ability to work independently and as part of a team. The successful candidate will be integrated within the Brain and Movement (BAM
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Group in the School of Mathematics, Statistics and Physics, part of the Joint Quantum Centre Durham-Newcastle, and make frequent visits to the experimental group in Durham. This position is available on a
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, gridded and reanalysis data) to facilitate the identification and statistical characterisation of health-relevant heat events. Your work will contribute to the development of city and national level spatial
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the UK. Activities will include: data preparation, statistical/epidemiological analysis, interpretation and dissemination. You should have post-graduate training and/or significant work experience in
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, statistical and computational skills, and ability to work independently and as part of a team. Successful candidates will be mentored by an experienced member of academic staff throughout their term in one
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to demonstrate some postgraduate-level training (or have equivalent experience) in the use of corprora and/or online acceptability judgements, including statistical analysis of results. You will be based