PDF - E-Community Toxicity Modelling - QC-154

Preferred Disciplines: Computer Science and Software Engineering (Post-Doc)
Project length: 2.5 years (5 units)
Approx. start date: As soon as possible
Location: Kelowna, BC and Quebec City, QC
No. of Positions: 1
Preferences: None
Company: Two Hat Security

About Company:

Two Hat Research has developed the next generation of moderation tools for virtual worlds and social networking apps. Our Community Sift product lets clients define which kinds of chat messages are acceptable and which are high risk. We are seeking MSc and PhD students to work on this research projects. We are particularly interested in pursuing multi-year collaborations.
We are committed to eliminating bullying from the web. We work with some of the largest video game, social media, and messaging companies on the internet and are scheduled to process 4 billion chat messages per day. We are deeply interested in publishing papers to showcase strong Canadian research. The work that these researchers will be doing will have a real-world impact.

Summary of Project:

The aim of this partnership with Université Laval in Quebec City is to develop the next generation of tools to detect, filter out, and anticipae toxic content in conversations in online communities. Since online content comes in dozens of languages, one major challenge will be detecting toxic messages in this multilingual context.
A great opportunity for a Post-Doctoral Fellow to conduct cutting-edge research in the Rapidly-Growing Tech Hub of the Beautiful Okanagan Valley in British Columbia

Research Objectives/Sub-Objectives:

  • Create toxicity detection tools that can work in a language agnostic way or that can easily be adapted to new languages.
  • Assist graduate students in designing and implementing natural language processing (NLP) tools that can work in multiple languages

Methodology:

    We do not require one specific methodology. However, the methodology selected must be capable of:

    • Handling noisy short user-written messages in a variety of languages
    • Handling a massive stream of messages in real time

    Expertise and Skills Needed:

    • Deep neural networks
    • Natural language processing
    • Research team leadership and management

    For more info or to apply to this applied research position, please

    1. Check your eligibility and find more information about open projects.
    2. Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform
    Program: