Faculty Assistant Professor, Statistics and Machine Learning Application in Education
The Department of Applied Psychology and Human Development (APHD) at the Ontario Institute for Studies in Education (OISE), University of Toronto invites applications for a full-time tenure stream position at the rank of Assistant Professor with a specialization in Statistics and Machine Learning Application in Education. The appointment will commence on July 1, 2022 or shortly thereafter.
Candidates must have completed a doctoral degree in Psychology, Statistics, Education, or a closely related discipline, in a field closely related to the area of specialization, by the date of appointment or shortly thereafter, with a demonstrated record of excellence in research and teaching. We seek applicants who have demonstrated research and practical expertise in the areas of data science and analytics, machine learning, natural language processing, network analysis, and statistical modelling methodologies. The successful candidate will be a researcher/educator with the demonstrated skills and background required to make creative and in-depth contributions to research, teaching, and student mentorship through applications of data science and analytics, machine learning, and applied statistics.
We seek candidates whose research and teaching interests complement and enhance our existing departmental strengths. The successful candidate will be expected to pursue innovative and independent research at the highest international level and to establish an outstanding, competitive, and externally funded research program. While we welcome applicants with demonstrated research excellence in a variety of academic backgrounds, including education, social sciences, humanities, engineering, computer science, computational linguistics, computational social science, health, and statistics, the research program of the successful candidate must emphasize the applications of data science, machine learning, and statistical modelling to educational and psychological phenomena.
Candidates must provide evidence of research excellence which can be demonstrated by a record of high-quality publications in top-ranked and field relevant journals or forthcoming publications meeting high international standards, presentations at significant conferences, awards and accolades, the submitted research statement, and strong endorsements from referees of high standing.
Candidates must have the demonstrated ability to combine disciplinary expertise with innovative, effective teaching methods that enhance the excellence and foster the diversity of their academic community. Evidence of excellence in university teaching must be clearly demonstrated through teaching accomplishments, the teaching dossier (with required materials outlined below) submitted as part of the application, as well as strong letters of reference.
In addition, application materials must demonstrate a candidate’s capacity for collegial and administrative service, preferably by providing evidence of the development of policies, processes, and/or resources for the effective functioning of administrative systems within an academic environment.
The successful candidate will contribute to the delivery of both core and interdisciplinary curricula within and across APHD programs and will work closely with the department chair and faculty to develop a research hub for technology-infused educational solutions, advancing multimodal, multichannel data science through machine learning and statistics.
Salary will be commensurate with qualifications and experience.
The Department of Applied Psychology and Human Development offers graduate programs in Counselling Psychology, Counselling and Clinical Psychology, Developmental Psychology and Education, School and Clinical Child Psychology, and Child Study and Education (a teacher education program). For more information, please visit the APHD web page at https://www.oise.utoronto.ca/aphd.
The Ontario Institute for Studies in Education has, for more than a century, made major contributions to advancing education, human development and professional practice around the world. OISE was ranked 3rd in the world for the subject of Education by the 2021 QS World University Rankings, holding first rank in the subject among Canadian institutions and among public universities in North America. With a network of approximately 100,000 alumni, over 3,000 students, 4 graduate departments, and 17 research centres, ours is an intellectually rich and supportive community, guided by the highest standards of scholarship and a commitment to equity and social justice. For more information, please visit OISE’s homepage at http://www.oise.utoronto.ca.
Established in 1827, the University of Toronto is Canada’s largest and most research-intensive university and the only Canadian university to be ranked among the top 20 universities in the world by the Times Higher Education World University Rankings. Located in and around Toronto, one of the world’s most diverse cities, the University of Toronto’s vibrant academic life is enhanced by the cultural diversity of its own and surrounding community.
All qualified candidates are invited to apply online at this link: https://jobs.utoronto.ca/job/Toronto-Assistant-Professor-Statistics-and-Machine-Learning-Application-in-Education-ON/552675717/. Applications must include a letter of application, an up-to-date curriculum vitae, a research statement outlining current and future research interests, three recent or forthcoming publications, and a teaching dossier (including a statement of teaching philosophy, teaching accomplishments, sample course materials, and teaching evaluations).
Applicants must provide the name and contact information of three references. The University of Toronto’s recruiting tool will automatically solicit and collect letters of reference from each once an application is submitted (this happens overnight). Applicants remain responsible for ensuring that references submit letters (on letterhead, dated, and signed) by the closing date.
Submission guidelines can be found at http://uoft.me/how-to-apply. Your CV and cover letter should be uploaded into the dedicated fields. Please combine additional application materials into one or two files in PDF/MS Word format. If you have any questions about this position, please contact the department at firstname.lastname@example.org.
All application materials, including letters of reference, must be received by Thursday, January 13, 2022, 11:59pm EST.
All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.
The University of Toronto is strongly committed to diversity within its community and especially welcomes applications from racialized persons / persons of colour, women, Indigenous / Aboriginal People of North America, persons with disabilities, LGBTQ2S+ persons, and others who may contribute to the further diversification of ideas.
As part of your application, you will be asked to complete a brief Diversity Survey. This survey is voluntary. Any information directly related to you is confidential and cannot be accessed by search committees or human resources staff. Results will be aggregated for institutional planning purposes. For more information, please see http://uoft.me/UP.
The University strives to be an equitable and inclusive community, and proactively seeks to increase diversity among its community members. Our values regarding equity and diversity are linked with our unwavering commitment to excellence in the pursuit of our academic mission.
The University is committed to the principles of the Accessibility for Ontarians with Disabilities Act (AODA). As such, we strive to make our recruitment, assessment and selection processes as accessible as possible and provide accommodations as required for applicants with disabilities.
If you require any accommodations at any point during the application and hiring process, please contact email@example.com.