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well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se/ida The position is based at the Division of Statistics and Machine Learning (STIMA). We conduct research
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of the Institut Polytechnique de Paris, is one of France's top 5 general engineering schools. The mainspring of Télécom Paris is to train, imagine and undertake to design digital models, technologies
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all units, develops dashboards reflecting key enrollment and revenue performance metrics for the university community, and ensures the accurate reporting of these data. MINIMUM QUALIFICATION Education
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. Other duties assigned on a rolling basis. Position Type/Expected Hours of Work: Part-time. 10 expected hours per week. Salary Range: $17.95 per hour. Required Education and Experience: Good academic
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abilities that are desirable, providing for an enhanced level of job performance, include: • Ability to develop new statistical and analytical methods leading to grant funding and accepted abstracts and
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University of Toronto | Downtown Toronto University of Toronto Harbord, Ontario | Canada | about 14 hours ago
, Epidemiology, and so on) by the time of appointment, or shortly thereafter, with a demonstrated record of excellence in research and teaching. Candidates in all areas of applied statistics will be considered
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an online application at https://hr.psu.edu/careers and should include: 1) a cover letter; 2) a curriculum vitae detailing the candidate’s educational background, employment history, publications, and grants
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and statistics. The EDUC sequence is designed to provide an interdisciplinary approach to offering basic to advanced methodology and statistics courses for all graduate students in the college. Position
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political and/or regional boundaries. This position will include resident and online instruction and normal university service. The teaching load during the academic year is three courses. Onsite teaching is
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to the following: SDSC6012 – Time Series and Recurrent Neural Networks SDSC6016 – Predictive Analytics and Financial Applications SDSC8013 – Statistical Methods for Categorical Data Analysis (For detailed course