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NICDS/GENERATION 5 RESEARCH INTERNSHIP POSITIONS The
National Institute on Complex Data Structures (NICDS) announces up to
two research internship positions in Data Mining, at Generation 5 Mathematical
Technologies. A typical duration would be 4 months starting in Jan,
2009. Michael Vainder, Generation 5 Mathematical Technologies, Michael dot Vainder at generation5 dot ca Review of applications will continue until the position is filled. Successful applicants will have the extremely valuable experience of working at a leading edge data mining company in Toronto. The focus is primarily on participation in production project in data mining field. Desirable background experience includes formal statistical training and programming experience in SAS. Familiarity with C++ would be an asset. STATISTICS CANADA/NICDS/MITACS RESEARCH INTERNSHIPS Deadline: June 15, 2009 Statistics Canada, The National Institute for Complex Data Structures (NICDS) and MITACS announce up to three research internship positions at the Methodology Branch within Statistics Canada. Interested Ph.D. students who have already passed the comprehensive exams at a Statistics department of a Canadian university, or Postdoctoral students affiliated with a Statistics department of a Canadian university, are invited to send their applications (covering letter, CV, and Application Form for Internship) by June 15, 2009 to: Dr. Georgia
Roberts Go to the following address to obtain an Application Form: http://www.stats.uwaterloo.ca/~mitacs/InternshipApplicationForm.htm Successful applicants will have the extremely valuable experience of working at Statistics Canada in Ottawa for a period of four to six months. The students will be involved in collaborative research with Statistics Canada and university researchers including their own supervisors. Research problems related to statistical methods for any stage of a complex survey will be considered, although of particular interest to Statistics Canada is the development of analytic tools for analysing longitudinal data arising from complex surveys. Some possible topics include: analysis of hierarchical survey data, structural equation modelling of survey data, small domain inference, analysis of duration data, and analysis of incomplete survey data. An experienced methodologist from the Methodology Branch will be assigned to work with each student during the stay at Statistics Canada. This collaboration will be mainly in the form of help for the more technical aspects of the doctoral dissertation, in helping with the handling of the data and in interpreting the results. Doctoral advancement and academic supervision would be the responsibility of the applicant and the thesis-supervising professor. For more information about the NICDS/MITACS project, Statistical Methods for Complex Survey Data, of which these internships form a part, go to http://www.stats.uwaterloo.ca/~mitacs
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