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Smith School of Business, Queen's University

Location: KingstonON K7L 3N6 Document ID: AD245-5ATR Posted on: 2019-06-2706/27/2019 Job Type: Regular

Job Schedule:Full-time
Will pay relocation expenses
Minimum Education: Not Specified2019-09-25
 

Tenure-Track Position in Management Analytics

Smith School of Business at Queen’s University (Kingston, Ontario, Canada) invites applications for a tenure-stream position in Management Analytics (formerly, Management Science and Operations), with preference for entry (Assistant Professor) level, and with a preferred starting date of July 1, 2020. The position is flexible in focus, and can be oriented either toward more “classical” Operations Management and Management Science, or toward Machine Learning and Artificial Intelligence; scholars with all methodological and conceptual interests in the topics (e.g., Ethics in AI) are invited to apply.

Qualifications

Candidates must have a PhD, or be near completion. The successful candidate will exhibit strong potential for innovative and high quality scholarly research leading to top-tier peer-assessed publications, as well as for outstanding teaching contributions and an ongoing commitment to academic and pedagogical excellence, in support of the School’s various public and private programs. The successful candidate will also be expected to make contributions through service to the School, the University, and/or the broader academic community.

Compensation

Salary will be commensurate with qualifications and experience. Appointees have access to substantial internal funds both for research and course development through Smith School of Business Research Program and our Faculty Development Fund. The School also provides faculty members with support in their applications to external research granting agencies such as the Social Sciences and Humanities (and/or Natural Sciences and Engineering) Research Councils of Canada, among others. Smith School of Business faculty members, including those in Management Analytics, have been quite successful with external research grant competitions.

Institution

Queen's University has a long and rich tradition of academic excellence, dating back to a royal charter granted by Queen Victoria in 1841. Smith School of Business is one of the world's premier business schools, with an outstanding reputation for innovation and quality. Our MSc and PhD programs in Management attract highly qualified research-oriented students in many fields of study. Our undergraduate Commerce program has among the highest entrance standards in Canada and is widely viewed as the country's best undergraduate business program. Queen’s has gained international recognition for its MBA and executive education programs and is fully accredited by AACSB and EQUIS. Smith School of Business is also home to centres focused on analytics, corporate governance, entrepreneurship and innovation, and social impact. The learning environment at Queen’s is supported by outstanding library and computing facilities (e.g., https://cac.queensu.ca/) More information can be found at: https://smith.queensu.ca/index.php, and general information about our faculty members is here: https://smith.queensu.ca/faculty_and_research/index.php

Management Analytics group

The Management Analytics group (formerly, Management Science and Operations Management) is comprised of strong researchers with particular expertise in revenue management and pricing, sustainability, energy markets, supply chain management and the interface of operations and marketing. Group members hold top editorial board memberships and have won multiple prizes and awards.

The Management Analytics group is at the forefront of the Analytics/Big Data/AI revolution with a portfolio of highly successful programs delivered out of the Smith location in downtown Toronto. These include the highly regarded Masters in Management Analytics (MMA, https://smith.queensu.ca/grad_studies/mma/index.php), North America’s first Masters in Management of Artificial Intelligence (MMAI, https://smith.queensu.ca/grad_studies/mmai/index.php), delivered jointly with Geoffrey Hinton’s Vector Institute for Artificial Intelligence (https://vectorinstitute.ai), and multiple Executive Education programs in Analytics.

The group is also actively involved in industry collaborations, primarily in financial services, through the Scotiabank Center for Customer Analytics, https://smith.queensu.ca/centres/scotiabank/index.php, and is otherwise tightly embedded in Toronto’s booming Analytics/AI scene.

The Cit(ies)

Smith School of Business operates in two locations:

Our main campus is in Kingston, Ontario – a unique Canadian city of 125,000 with a distinct blend of history, recreation, industry and learning. Situated on the shores of Lake Ontario, Kingston offers unique waterfront living with many recreational and cultural opportunities. It is within a 2h train ride (~2.5-3h drive) to the commercial, industrial and political hubs of Toronto, Montreal, and the nation’s capital, Ottawa, and a thirty-minute drive from the international bridge linking Ontario and upstate New York. The city is also the origin of the historic Rideau Canal system – a UNESCO International Heritage site. For more information please see: https://www.cityofkingston.ca/explore/about-kingston

Our second location is in downtown Toronto, where much of the Management Analytics group’s activities take place. As demonstrated by various international rankings and reports, Toronto is one of the best cities in the world to live and work. For more information please see: https://www.toronto.ca/city-government/data-research-maps/toronto-progress-portal/world-rankings-for-toronto/

 

How to Apply

The effective date of the appointment will be July 01, 2020, but is flexible.

The University invites applications from all qualified individuals. Queen's is committed to employment equity and diversity in the workplace and welcomes applications from women, visible minorities, Aboriginal peoples, persons with disabilities, and LGBTQ persons. All qualified candidates are encouraged to apply; however, in accordance with Canadian immigration requirements, Canadian citizens and permanent residents of Canada will be given priority.

The University will provide support in its recruitment processes to applicants with disabilities, including accommodation that takes into account an applicant’s accessibility needs. If you require accommodation during the interview process, please contact: Roshan Udit at rgu1@queensu.ca. Academic staff at Queen’s University are governed by a Collective Agreement between the University and the Queen’s University Faculty Association (QUFA), which is posted at http://queensu.ca/facultyrelations/faculty-librarians-and-archivists/collective-agreement and at http://www.qufa.ca.  

To comply with Federal laws, the University is obliged to gather statistical information about how many applicants for each job vacancy are Canadian citizens / permanent residents of Canada. Applicants need not identify their country of origin or citizenship; however, all applications must include one of the following statements: “I am a Canadian citizen / permanent resident of Canada”; OR, “I am not a Canadian citizen / permanent resident of Canada”. Applications that do not include this information will be deemed incomplete. Your application cover letter must include one of these two citizenship statements.

Applicants should submit:

  • A cover letter, including one of the two statements regarding Canadian citizenship/permanent resident status specified in the previous paragraph
  • A current Curriculum Vitae, including a list of publications
  • A statement of current and prospective research interests
  • Evidence of research, such as copies of sample publications, working papers, or a dissertation proposal
  • A statement of teaching interests and experience, including course outlines and evaluations, if available
  • Three letters of reference

Deadline for applications: September 4, 2019
Note: only selected candidates will be contacted for interviews.

Submitting your application

Please submit your application package via Interfolio Faculty Search through the following link: https://apply.interfolio.com/64506