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position in the field of Machine learning meets choice models available. Project description Nonparametric statistical learning provides a flexible and data-driven approach to choice modeling. Recent
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sciences, hydrology, statistics, applied mathematics, agronomy, or related fields. Written and oral proficiency in English is required. Interest and previous experience in developing mechanistic models
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control problems in, for example, financial and energy markets, Collaborate with a team of experts in fields such as stochastic analysis, statistics, finance and computational science, Participate in
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"with memory" are of importance in several disciplines, such as for financial and statistical modelling. However, due to the correlation structure their computational simulation is very challenging
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learning meets choice models available. Project description Nonparametric statistical learning provides a flexible and data-driven approach to choice modeling. Recent advancements have improved its economic
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, sociology, gerontology, political science, statistics, public health or health sciences/medicine) or completed courses of at least 240 higher education credits, of which at least 60 higher education credits
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; Midlands Graduate School Doctoral Training Partnership | Nottingham, England | United Kingdom | about 18 hours ago
performance and green innovation. It also explores how these effects change when combined with environmental regulations and innovation incentives. The project will employ statistical analysis and econometric
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and theoretical skills in statistics and proficiency R programming Strong experience or interest in big data, preferable, omics data analysis. Fluency in English LanguagesENGLISHLevelExcellent
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research proposal. You must submit one application per studentship, you cannot apply for multiple studentships on one application. Contact Details Dr Adam Stokes , School of Mathematics, Statistics and
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could lower the risk of future outcomes. The goal of this project is to apply multivariate statistics and quasi-causal designs to examine whether various interventions might be causally linked to lower