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Post-Doctoral Fellow - Analytics + AI Ecosystem

Post-Doctoral Fellow - Analytics + AI Ecosystem

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 & 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

$60,000 minimum with consideration given to industry experience. Additional funding pending.

Start Date and Duration of Appointment:

Start date is negotiable; 2-year postdoc term.

Equity Statement

EMPLOYMENT EQUITY: 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 people, women, persons with disabilities, and 2SLGBTQ+ persons.

ACCOMMODATION IN THE WORKPLACE: The University has policies in place to support its employees with disabilities, including an Accommodation in the Workplace Policy and a policy on the provision of job accommodations that take into account an employee's accessibility needs due to disability. 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 Daniel McBride at daniel.mcbride@queensu.ca or 613.533.3298.

How to Apply

Deadline for applications:

November 01, 2021

Applicants should submit:

  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.

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. 

Submit your application to:

Daniel McBride
Associate Director
Scotiabank Centre for Customer Analytics
daniel.mcbride@queensu.ca