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Post-Doctoral Fellow - Analytics and AI Ecosystems

Post-Doctoral Fellow

Job Title: Post-Doctoral Fellow Department: Analytics + AI Ecosystem Supervision and Academic Unit: Dr. Stephen Thomas, Smith School of Business Description of Area or Topic of Research: The Smith School of Business at Queen’s University invites applications for an Industrial Postdoctoral Fellow (iPDF) position to take a leadership role in the Digital Technology Supercluster project Wellbeing.ai. The iPDF will use modern techniques in artificial intelligence, machine learning and more specifically, natural language processing, to tackle research problems and advancements in the following (yet not limited to) areas under the supervision of Dr. Stephen Thomas, his collaborators and industry partners: Automatic topic generation Virtual assistant diagnostics Recommendation/Inference engines optimization Voice to text This role will position the iPDF to transition to industry or to a teaching role at a research institution. The iPDF will conduct research to support new methodology and perform benchmarking comparisons in real-data exercises provided by two leading industry partners: Wysdom.AI and lululemon athletica. Ultimately, the research will support the development of a model to understand wellbeing, enabling a ‘digital brain’ (virtual assistant) to understand human interactions to deliver an immersive and personalized coaching experience. The iPDF will create and edit written materials for publications as well as give talks to engage the broader Smith School of Business Analytics and AI community. The iPDF is expected to be independently motivated to execute high-quality research in a collaborative environment.  

Qualifications

The successful candidate should have a PhD completed within the last 5 years in Computer Science, Machine Learning, Statistics, Operations Research, Engineering or a related field. They will ideally have familiarity with supervised and unsupervised machine learning, deep learning, natural language processing, chatbots, recommender systems, and related AI/ML and statistics literatures. Experience with both shallow NLP procedures (e.g., TF-IDF) and deep NLP procedures (e.g., RNNs, large pre-trained language models such as GPT-3) is preferred. Experience in Python is preferred.

This position will require the ability to work independently as well as in teams and to communicate effectively with a variety of project stakeholders both internal and external to Smith. The ability to communicate technical material effectively to a broad audience as well as the ability to set goals, track progress and prioritize as necessary to meet the deadlines are highly desired.

Compensation

$90,000 minimum with consideration given to industry experience. Additional funding pending.

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

The City

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

How to Apply

The effective date of the appointment will be February 01, 2022, but is flexible.

Applicants should submit:

  • Start Date and Duration of Appointment: Start date is negotiable; 2-year postdoc term

    Required Documentation:

    1. Curriculum vitae
    2. Ph.D. thesis, thesis papers, or writing sample if available
    3. Cover letter, including a brief description of research interests, how you heard about this position, when you can start, and how this position will help advance your career goals.
    4. Graduate transcripts
    5. Two recommendation letters: have referees email daniel.mcbride@queensu.ca directly.

    Application Deadline: Review of applications is open and will continue on a rolling basis. The first review will be on November 1, 2021, though applications submitted after this will still be considered until the position is filled. 

Daniel McBride - daniel.mcbride@queensu.ca

The University invites applications from all qualified individuals. Queen's is strongly committed to employment equity, diversity, and inclusion in the workplace and encourages applications from Black, racialized/visible minority and Indigenous/Aboriginal peoples, women, persons with disabilities, and 2SLGBTQ+ 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: Kevin Bissonette at kb106@queenu.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 https://queensu.ca/facultyrelations/faculty-librarians-and-archivists/collective-agreement and at https://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.

In addition, the impact of certain circumstances that may legitimately affect a nominee’s record of research achievement will be given careful consideration when assessing the nominee’s research productivity. Candidates are encouraged to provide any relevant information about their experience and/or career interruptions.