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; University of Sussex | The City of Brighton and Hove, England | United Kingdom | about 7 hours ago
PhD studentship in the Groups “Numerical Analysis and Scientific Computing” and “Mathematics Applied to Biology” at the University of Sussex (UK). PhD project Statistical inference has proved to be
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of cutting-edge statistical methods and machine learning algorithms inspired by massive healthcare datasets. Key Responsibilities Develop innovative statistical methods and machine learning algorithms
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SECURITY CRIME STATISTICS: Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Pennsylvania Act of 1988, Penn State publishes a combined Annual Security
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usefulness of the forecast, and perception of forecast performance by the public. Statistical post-processing techniques can help to reduce forecast errors by training machine learning models on data sets
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generalisability compared to traditional adaptive control methods. Rigorous theoretical and statistical analysis will be carried out to prove the effectiveness of these proposed techniques. Hence, a strong
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control methods. Rigorous theoretical and statistical analysis will be carried out to prove the effectiveness of these proposed techniques. Hence, a strong foundation in mathematical and control theory is
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deficits, such as those caused by glaucoma. You will make use of experimental and theoretical techniques, such as sensorimotor analysis and Bayesian statistical modeling, to create diagnostic and screening
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undergraduate students. Assist with grant writing, NSF submissions and reporting. Required Qualifications Master's degree in Data Science, Computer Science, Statistics, Computational Social Science, Communication
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. Eligibility Criteria A 2:1 honours degree, or international equivalent, in a relevant subject (e.g. health sciences, epidemiology, statistics, psychology, medicine, pharmacy, nursing, midwifery, allied health
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computer skills (Microsoft Office Products, Canva) Desired Qualifications Preferred qualifications Knowledge of statistical analysis software (e.g., SPSS, R) and data visualization techniques l skills, with