The Faculty of Science at the University of Regina invites applications for nomination to a Tier 1 Canada Research Chair (CRC) in Computational Learning Theory.
As an employer committed to employment equity, we are seeking applications from women scientists for this position.
As the 2016 evaluation of the CRC program noted, “more work is needed to address barriers to access for designated groups”. In order to address gender inequity in Computer Science and alleviate the under-representation of women in Tier I CRC positions, this position is targeted to women. Designating this position supports the Government of Canada’s efforts to improve equity, diversity, and inclusion within the research community and honours our commitment to the Dimensions principles.
Candidates must formally self-identify to be considered for the position.
Computational Learning Theory is a branch of artificial intelligence that deals with the design and analysis of algorithms that enable computers to infer/discover/learn patterns from sample data. This very active area of Computer Science has wide-ranging applications to a variety of fields, including but not limited to bioinformatics, health informatics, and finance. In contrast to big data analysis, which involves randomly selected samples, Computational Learning Theory addresses knowledge acquisition and decision making based on relatively small amounts of carefully selected data.
Candidates are required to hold a Ph.D. in Computer Science or a related field. Candidates are expected to be committed to excellence in the three pillars of academia (research, teaching, and service). All three criteria will be used to evaluate and rank the applications, but the primary emphasis will be on research.
The successful candidate will be expected to prepare a Tier I CRC application that articulates an original, innovative, and high quality research program.