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postgraduate courses; supervise research students; and perform any other duties as assigned. Requirements A PhD in Mathematics/Applied Mathematics/Statistics with an excellent record in research, teaching and
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are preferred. Ability to teach courses in statistics, including basic courses up to lower-level masters courses, is strongly desired. Normal duties will include teaching 4 courses per semester (12 credit hours
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Minimum Education and Experience The successful candidates must have a Masters, preferably PhD degree in Statistics or a related field such as Mathematics or Business. Prior teaching experience is preferred
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field or equivalent combination of education and experience (Required) PhD degree in quantitative methods, statistics or a related field (Preferred) Special Conditions for Employment Background Check
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expected to contribute to teaching and curriculum development for undergraduate and postgraduate programmes in Applied Mathematics and Statistics, to play a lead role in collaborative research projects and
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, Statistics I, Engineering Statistics. Preferred Qualifications Demonstrated excellence in teaching and/or industrial experience involving applied statistics. Doctoral degree in Statistics. Special Conditions
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the Collaborative Doctoral Partnerships programme, training researchers at the science-policy interface. Where to apply Website https://jobs.unibas.ch/offene-stellen/phd-position-ai-driven-pathways-to-health
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Statistics-related degrees: BS in Mathematics with a Statistics Emphasis MS in Statistics PhD in Statistical Sciences (with interdisciplinary data analytics focus) We are committed to teaching at all levels
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in grant-writing and annual reports Perform other duties as assigned Minimum Qualifications: Education and Experience: PhD degree in Mathematics, Applied Mathematics, Computational Science, Statistics
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/nanofabrication, characterization and the development of miniaturized devices. Experience with multivariate analysis, computational methods or statistical techniques is highly desirable. The PhD projects are highly