Tenure Track Position in Industrial Engineering Focusing on Data Science and Analytics
Ryerson University is strongly committed to fostering diversity within our community. We welcome those who would contribute to the further diversification of our staff, our faculty and its scholarship including, but not limited to, women, visible minorities, Aboriginal people, persons with disabilities, and persons of any sexual orientation or gender identity. Please note that all qualified candidates are encouraged to apply but applications from Canadians and permanent residents will be given priority.
Located in downtown Toronto, Ryerson University (www.ryerson.ca) is a distinctly urban, culturally diverse teaching and research institution. The University is deeply connected to the city and beyond, attracting global talent and opportunities. Programs are kept relevant to changing careers, professions and scholarly disciplines. Students, faculty and staff challenge the status quo with new solutions and ways of thinking. Partnerships with community, industry, government, and professional practice drive research and innovation that responds to real-world problems. Our diverse learning community collaborates across disciplines and with external partners, taking thoughtful risks and promising ideas and turning them into tangible solutions that have a positive and meaningful impact on society. In their programs and through experiential opportunities, students learn to work collaboratively in teams - with different backgrounds and perspectives – to solve complex problems, think critically and communicate clearly, gaining the skills and knowledge to build careers, enter professions or to launch ventures and create jobs.
The Opportunity: The Department of Mechanical and Industrial Engineering (https://www.ryerson.ca/mie/) in the Faculty of Engineering & Architectural Science at Ryerson University invites applications for a tenure-track position at the rank of Assistant Professor in Industrial Engineering focusing on Data Science and Analytics, effective July 1, 2019, subject to final budgetary approval.
The Department of Mechanical and Industrial Engineering (MIE) has 38 faculty members and offers four-year accredited programs leading to Bachelor of Engineering (BEng) degrees in Mechanical Engineering and Industrial Engineering. The Department also offers graduate programs leading to a Doctor of Philosophy (PhD) degree, Master of Applied Science (MASc) degree, and Master of Engineering (MEng) degree. The Mechanical and Industrial Engineering Department is home to about 1,170 undergraduate and 150 graduate students. The department is also the home of the Data Science Laboratory (DSL) and a certificate program in Data Analytics, Big Data and Predictive Analytics. DSL engages in government and industry funded research in machine learning.
Responsibilities: The successful candidate will have obligations to both the Department of Mechanical and Industrial Engineering and the interdisciplinary graduate program in Data Science and Analytics. The applicant will carry out teaching duties in the Data Science and Analytics program. They will be expected to carry out research, service, mentoring and supervision of students equally between the Department of Mechanical and Industrial Engineering and the Data Science and Analytics graduate program. The successful candidate is also expected to establish and maintain a dynamic, externally-funded research program, as well as fostering an inclusive, equitable, and collegial work and learning environment.
Qualifications: Candidates must hold a Ph.D. degree (or be near completion) in Industrial Engineering, Computer Science or a related field. Postdoctoral experience is an asset. Although it is not required, holding a P.Eng. at the time of appointment or being eligible to become a P.Eng. would be an asset. Candidates must have a demonstrated commitment to uphold the values of Equity, Diversity, and Inclusion in teaching, research and service. This includes the ability to foster creative and collaborative intellectual inquiry by bringing diverse knowledge, experiences and perspectives to learning activities and research projects. Candidates must demonstrate well developed research and teaching abilities in data science and analytics with expertise in machine learning, building high performance algorithms, and dealing with big datasets using advanced parallel computing platforms and tools (i.e. Hadoop, Pig, Hive, etc.) in various application domains. The successful candidate will have the ability to contribute to Ryerson’s University’s interdisciplinary graduate program in Data Science and Analytics. Candidates must hold a strong research profile (e.g., evidence of an emerging scholarly record, ability to establish and maintain an independent, externally funded research program) in machine learning, evidence of high-quality inclusive teaching and student training, and a capacity for collegial service.
Equity at Ryerson: At the intersection of mind and action, Ryerson is on a transformative path to become Canada’s leading comprehensive innovation university. Integral to this path is the placement of equity, diversity and inclusion as fundamental to our institutional culture. Our current academic plan outlines each as a core value and we work to embed them in all that we do.
Ryerson University welcomes those who will assist us to expand our capacity for diversity in the broadest sense. In addition, to correct the conditions of disadvantage in the field of Engineering in Canada, we encourage applications from members of groups that have been historically disadvantaged, including First Nations, Métis and Inuit peoples in Canada, Indigenous peoples of North America, racialized persons, persons with disabilities, and those who identify as women and/or 2SLGBTQ+. Indigenous candidates who would like to learn more about working at Ryerson University are welcome to contact Ms. Tracey King, M.Ed., Aboriginal HR Consultant, Aboriginal Recruitment and Retention Initiative, at mailto:firstname.lastname@example.org.
Ryerson recognizes that scholars have varying career paths and that career interruptions can be part of an excellent academic record. Candidates are encouraged to provide any relevant information about their experience and/or career interruptions to allow for a fair assessment of their application.
The university is committed to accessibility for persons with disabilities. We want to ensure that all participants are able to engage fully in interviews and other activities that are part of the process. If you have any accommodation requests, please contact Melissa Rotundo, Sr. HR Consultant at mailto:email@example.com. All requests for accommodation will be treated confidentially.
How to Apply: Please note that all qualified candidates are encouraged to apply; however, applications from Canadians and permanent residents will be given priority.
Applicants should submit their application online via the Faculty Recruitment Portal (click on Apply below to begin). The application must contain the following:
A cover letter, which includes a description of how commitment to equity, diversity and inclusion has been demonstrated in teaching, research and service.
A curriculum vitae
Three examples of materials produced to disseminate research, e.g. publications, conference presentations, etc.
A research statement (maximum 3 pages)
A teaching statement (maximum 2 pages)
Supervisor or peer teaching evaluations, if any
Names and contact information of three individuals who may be contacted for references.
Indication in your application if you are a Canadian citizen or a permanent resident of Canada
Confidential inquiries can be directed to the Chair of Department Hiring Committee (DHC), Dr. Sharareh Taghipour at firstname.lastname@example.org. The review of applications will begin April 9, 2019 and continue until the position is filled.
Any inquiries regarding accessing the Faculty Recruitment Portal can be sent to Laurie Shemavonian, Human Resources Advisor, at email@example.com.
This position falls under the jurisdiction of the Ryerson Faculty Association (RFA) and relevant information can be found as follows: RFA Website - www.rfanet.ca; RFA Collective Agreement - https://www.ryerson.ca/content/dam/faculty-affairs/rfa-collective-agreement/RFA_CA_2015_to_20 18.pdf; RFA Benefits - https://www.ryerson.ca/hr/employee-resources/rfa/full-time-LTF/benefits/
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as one of Canada’s Best Diversity Employers and a Greater Toronto’s Top Employer for 2015, 2016 and 2017. To learn more about our work environment, colleagues, leaders, students and innovative educational environment, visit www.ryerson.ca, check out @RyersonU, @RyersonHR and @RyersonECI on Twitter, and visit our LinkedIn company page.