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degree in Social Sciences, Statistics, Social Work, Sociology, Psychology, Criminology or related disciplines, with at least one-year post-graduate research experience. Those with interest in the topics
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the possibility of renewal, subject to satisfactory performance and funding availability. Applicants should possess a Ph.D. degree in Social Work, Psychology, Statistics, Public Health, or a related discipline
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methods of data analytics (e.g., statistics, stochastic analysis, Bayesian statistical analysis), physically-based hydrology and water quality models, and the use of machine learning tools for modeling flow
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an initially solid-like state firsts yields and starts to flow, and in particular on the statistical physics of how initially sparse plastic events in an otherwise elastic background then spatio
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Professor of Veterinary Integrative Biosciences (College Station, TX), respectively. Technical supervision on data analysis, statistics, and database management will be provided by the Assistant Professor
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of Social Sciences but will also work also closely with colleagues in Social Statistics and Computer Science. The work shall be carried out in line with the grant application granted originally by the ERC (as
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(e.g. ADOS-2, ADI-R), is strongly preferred. Knowledge, Skills and Abilities: Knowledge of Microsoft Office suite. Familiarity with statistical packages (e.g., SPSS, R) Ability to work as a member of a
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maternal and child health; funded by the National Institutes of Health and the Centers for Disease Control and Prevention. The post-doctoral associate will provide expertise in statistical analyses and
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team composed of researchers, engineers, bioinformaticians, biostatisticians and a project manager. The ideal candidate should hold a Ph.D. in Population genomics, Statistical Genomics, Evolutionary
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knowledge of statistical techniques for data analysis Experience in detector performance or trigger systems for high energy or nuclear physics experiments Experience with machine learning techniques and tools