Canada Research Chair Tier 1 - Computational Learning Theory
University of Regina
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. The home academic department of the successful candidate will be the Department of Computer Science. Candidates should normally have reached the rank of full Professor but Associate Professors who are expected to be promoted to the full Professor level within one or two years of the nomination may also be considered.
The Canada Research Chair Program (www.chairs-chaires.gc.ca) has been established by the Government of Canada to foster research excellence in Canada. Tier 1 chairs are for a term of seven years, and are renewable for up to one additional seven-year term. Thereafter, the chair-holder will hold a regular faculty appointment. As explained in more detail below, Tier 1 chairs are outstanding and innovative world-class researchers whose accomplishments have made a major impact in their fields and are recognized internationally as leaders in their fields. They have superior records of attracting and supervising graduate students or postdoctoral fellows and, as chair-holders, will be expected to attract, develop, and retain excellent trainees, students and future researchers, and propose an original, innovative research program of the highest quality.
The University of Regina’s Strategic Research Plan for 2020-2025 (All Our Relations: kahkiyaw kiwâhkômâkaninawak) places ’Discovery’ as the first area of focus and includes Excellence in Research and Teaching as the first strategic priority in this area. The University of Regina is a global leader in Artificial Intelligence and Machine Learning, with significant strength in the area of Computational Learning Theory.
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.
Given that scholars have varying career paths and that career interruptions can be part of excellent academic records, candidates are encouraged to provide any relevant information about their experience or career interruptions (e.g., parental leave or leaves due to illness) to allow for a fair assessment of their application. All chairs are subject to review and final approval by the Canada Research Chairs Program.
The successful candidate must be an outstanding and innovative world-class researcher whose accomplishments have made a major impact in the field of Computational Learning Theory. The candidate must be recognized internationally as a leader in this field. They must have a superior record of attracting and supervising graduate students or postdoctoral researchers. As the chair, the successful candidate will be expected to attract, develop, and retain excellent trainees, students, and future researchers, and propose an original, innovative research program of the highest quality.
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.
Candidates are required to provide a CV that demonstrates a strong research record via high-impact peer-reviewed publications on topics closely aligned with Computational Learning Theory, external funding for this research, supervision of graduate students or postdoctoral researchers, and international recognition for leadership and contributions to this field. Candidates are required to provide a seven-year research plan (up to five pages long) that has the potential to be supported by a Tier I Canada Research Chair. This plan should include details on a research agenda to develop and undertake innovative programs of research that are of the highest quality, to recruit and retain graduate students, and to secure external funding.
Candidates are expected to provide evidence of teaching expertise and an established teaching philosophy. The successful candidate will have a reduced teaching load during the tenure of the Tier I Canada Research Chair but will still be expected to teach one course annually at the undergraduate level in the area of Artificial Intelligence and one course annually at the graduate level with a specific focus on Computational Learning Theory.
Candidates are expected to demonstrate a commitment to academic service through committee work, peer review activities, and the support of other academic work. The successful candidate will have a reduced service load during the tenure of the Tier I Canada Research Chair but will still be expected to be a willing participant in academic service, both within the Department/University and within the broader academic community.
The successful candidate will be expected to prepare a Tier I CRC application that articulates an original, innovative, and high quality research program.
For additional information about the position and the research environment in support of the position, see: www.uregina.ca/science/crc-search-2021.html.
Special Application Instructions
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 (https://www.nserc-crsng.gc.ca/NSERC-CRSNG/EDI-EDI/Dimensions_Dimensions_eng.asp).
Applications for this position are made online: www.uregina.ca/hr/careers/opportunities.html (under Academic/Staff/Research Positions).
Applications should include a cover letter, a curriculum vitae, a summary of research achievements to date, a brief outline of the proposed research, and the names and contact information of three referees.
Review of applications will commence on 07 June 2021. Candidates must formally self-identify to be considered for the position. Questions about the position should be addressed to the chair of the search committee, Dr. Howard Hamilton (email@example.com).
The University of Regina is committed to development of a representative and inclusive workplace that reflects the richness of the community that we serve. For this competition, the University welcomes applications from all women, including women with disabilities, members of visible minorities, and Indigenous persons. The University’s accommodation policies are available at https://www.uregina.ca/policy/browse-policy/policy-EMP-080-005.html (contact: Danni Kenzle, Danni.Kenzle@uregina.ca, 306-585-4166.
The University of Regina is committed to an inclusive workplace that reflects the richness of the community that we serve. The University welcomes applications from all qualified individuals, including individuals within the University’s employment equity categories of women, persons with disabilities, members of visible minorities, Indigenous persons, individuals of diverse gender and sexual orientation and all groups protected by the Human Rights Code.