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Department: The mission of the George Mason University Department of Statistics is to pursue sound and reproducible research in statistics and data science; train and educate the next generation of statistics
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, preferably PhD degree in Statistics or a related field such as Mathematics or Business. Prior teaching experience is preferred. Interested individuals are to apply online at: https://jobs.rutgers.edu/postings
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opportunity to see mathematical models come alive, guiding experiments as they happen. Teaching: The position includes a small teaching duty in Statistics → includes enhanced salary compared to standard PhD
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Qualifications n A PhD in Mathematics, Statistics, Applied Mathematics, or a related field at the time of appointment. n Strong professional ethics and academic reputation. n For Associate/Full Professor positions
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and education in both statistics and machine learning, at the undergraduate, advanced and PhD levels. The employment When taking up the post, you will be admitted to the program for doctoral studies
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FieldPhysics » BiophysicsEducation LevelMaster Degree or equivalent Skills/Qualifications - Eligibility for doctoral studies in Physics, Biophysics - Not already holding a doctoral degree (PhD) - Completed
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(PhD) - Completed higher education (Bachelor's/Master's) in Physics, Chemistry, Biochemistry, Computer Science Specific Requirements - Other specific job requirements: Exceptional qualifications in
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based at our Edinburgh campus in the UK. Education, Qualifications and Experience Essential E1. PhD in Actuarial Science, Statistics, or a related field. E2. Track-record of high-quality research in
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Education and/or Training: Bachelor's degree in bioinformatics, cheminformatics, statistics/computer science (with a background in biological sciences or chemistry) or related field. Master's degree or PhD
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the academic year. Requirements A PhD degree in related disciplines with proven teaching experience at the university level is required. Salary and Conditions of Service Salary offered will be highly competitive