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, with staff drawn variously from economics, sociology, social policy, demography, psychology, anthropology and social statistics. We promote problem-solving interdisciplinary research on particular themes
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degree in a field related to Public Health Nutrition, Epidemiology, or Public Health, with demonstrated strengths in geospatial and statistical methods. Demonstrated proficiency in Stata, R, or other
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addressing complex health and social care challenges of the 21st century. We employ traditional statistical and epidemiological methods, alongside cutting-edge artificial intelligence algorithms to gain
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, psychology, sociology, epidemiology or statistics) along with experience in planning and developing independent, original, significant and rigorous contributions to your subject area and publishing empirical
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. Responsibilities will include data collection and processing using statistical software such as R or Python. The role is funded by UK Research and Innovation under its “Creating Opportunities Evaluation Development
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of multi-variate statistics as well as script programming Excellent communication skills in English Good teamwork skills and willingness to collaborate across disciplines. Application details: Applications
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conduct and statistically analyse microbial evolution and ecology experiments using synthetic and natural communities. The temperature dependence of microbial respiration remains one of the largest
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to engage with diverse audiences, including individuals with lived experiences of depression, through public engagement and public outreach initiatives. As a valued member of our team within the Statistical
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inequality. Responsibilities will include data collection and processing using statistical software such as R or Python. The role is funded by UK Research and Innovation under its “Creating Opportunities
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of Masters Programmes and a substantial number of postgraduate research students. We undertake research on a wide range of issues relating to human evolution, with a fo cus on model-based statistical inference