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available option. Applicants with a range of academic subject backgrounds are welcomed, including natural sciences, engineering, statistics and applied mathematics with experience and/or growing interest in
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, computer science, statistics, or a related field together with strong programming skills in Python, R, or similar languages, and proficiency in high-performance computing. You will have experience in large-scale
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administrative tasks. Qualifications and Skills You should have a PhD (or be near completion) in Sociology, Psychology, Education, Statistics, or any related field. You should have a strong interest in empirical
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links between online polarization and a multidimensional perspective on mental health and wellbeing. Using advanced methods in statistical modeling, NLP, HCI, and experimental design, it will also test
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knowledge and hands-on experience in data collection, secure data storage, and statistical analysis, adhering to open science practices and data protection regulations. Understanding of Randomised Controlled
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design, statistical sampling and analysis of large, multi-taxa biodiversity datasets. Expertise in landscape-level biodiversity and production analyses using R, QGIS, Google Earth Engine. Extensive
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the development of study protocols in collaboration with PPIE representatives for ethical review submission. Strong knowledge and hands-on experience in data collection, secure data storage, and statistical
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show evidence of understanding, expression and application of concepts and methods. Strong data analysis skills, especially in applied econometrics and statistical methods within health economics are
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skills, especially in applied econometrics and statistical methods within health economics are essential as is the ability to work effectively independently and collaboratively. Diversity Committed
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electronic health records (EHRs) from multiple UK hospital centres using advanced data analytics including machine learning, deep learning, and statistical techniques—with a particular emphasis on deep