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an available option. Applicants with a range of academic subject backgrounds are welcomed, including natural sciences, epidemiology, engineering, statistics and applied mathematics with experience and
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Experience in statistical or scientific programming (ideally R and/or Python) Experience in analyzing large and/or complex datasets Interest in quantifying uncertainties for computer models and/or climate
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Agency (ARIA). The PROTECT project (Probabilistic Forecasting of Climate Tipping Points) brings together cutting-edge AI, statistical, and machine learning techniques with climate modelling, aiming
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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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the risks. You will have: a PhD in one of the relevant STEM disciplines, such as mathematics, statistics, computer sciences, theoretical food, ecological or physical sciences, etc. skills in mathematical
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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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specialist knowledge in a relevant subject area. With knowledge of statistics and ability to use statistical packages for analysing data, you will have excellent communication skills and the ability to work co
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specialist knowledge in a relevant subject area. With knowledge of statistics and ability to use statistical packages for analysing data, you will have excellent communication skills and the ability to work co
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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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PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets Experience in statistical or scientific programming (ideally R and/or