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, benchmarking the ML-based, enhanced catalogues and development of statistical metrics to describe their strengths/weaknesses. We are looking for candidates qualified to PhD level in a topic related to earthquake
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collaborative, interdisciplinary setting. You must hold (or be about to receive) a PhD in Statistics, Data Science, Computer Science, or a related discipline. Substantial experience applying machine learning
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will involve collation, management and statistical analysis of datasets, sourcing of environmental, geographical and land use datasets to complement field-collected data, publishing first author papers
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student education. We are methodologically and disciplinarily diverse, with faculty in sociology, anthropology, international relations, political science, statistics, economics, social psychology, social
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candidate will have a PhD in a strongly quantitative discipline, but applications from candidates close to submitting their PhD are also welcome. Familiarity with deep learning methodologies is essential, as
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home for up to half of your working week, providing a balanced work environment. We're looking for an individual that has (or is soon to receive) a PhD in a statistical subject (equivalently, for
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background (PhD or postdoctoral research) in genetic/molecular epidemiology or statistical genetics or population health science Experience using statistical programming languages (such as R and python
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and collaboration. Duties and responsibilities This is an exciting opportunity to conduct ambitious research at the interface of information theory, statistical machine learning and robotics
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. MSc/PhD) in data science, statistics, epidemiology, or a related subject, have significant experience in analysis of large complex epidemiological datasets, using Stata, R or SAS, and have excellent
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the opportunity to undertake co-supervision of PhD students within the group and develop management skills. The ideal candidate: We are looking for candidates with a PhD in computational or Plant