About This Role: This is an opportunity to help build Indigenous-led AI research at Western University through the OTEKH Lab and the Haudenosaunee POD of the international Abundant Intelligences partnership. The Research Associate - Lab Tech will contribute to projects involving Indigenous AI, large language models, machine learning, Indigenous language revitalization, relational digital archives, Indigenous data sovereignty, generative systems, and community-engaged research-creation. Rather than serving only in a technical support role, the successful candidate will help shape research questions, develop and test AI tools, support Indigenous language and archive initiatives, build technical workflows, and contribute to major interdisciplinary projects connecting advanced technologies with Indigenous knowledge, community priorities, land-based research, and creative practice. This position is well suited to a graduate researcher who is excited by experimentation, capable of independent technical work, and interested in helping establish long-term Indigenous research infrastructure, methods, and possibilities for AI.
Responsibilities: Research Associates (RAs) are central members of the Abundant Intelligences Project and the Haudenosaunee POD at the OTEKH Lab at Western University. RAs will contribute to leading-edge interdisciplinary research in artificial intelligence, machine learning, large language models, Indigenous language revitalization, relational archives, and research-creation. Working collaboratively with faculty, community partners, students, artists, and technical researchers, RAs will help develop projects from early research design through technical development, testing, production, documentation, and public presentation. This role is intended for students who can bring both technical capacity and creative, critical, and relational approaches to AI research. The position offers flexibility around academic schedules, opportunities to take leadership on specific research initiatives, and responsibilities that may include mentoring and coordinating undergraduate research assistants. RAs are expected to contribute ideas, work collaboratively across disciplines, and help shape the long-term development of the Lab’s research infrastructure and projects.
The role may include:
- Assisting with the design, development, testing, and deployment of AI and machine-learning research projects, including work with large language models, generative systems, computer vision, local/offline AI tools, and interactive media environments.
- Supporting research in Indigenous language revitalization, including the development of language-learning tools, language datasets, model testing, interface design, and carefully governed approaches to language materials.
- Contributing to the design and development of relational digital archives, including systems for community-led access, layered permissions, metadata, cultural protocols, Indigenous data sovereignty, and long-term stewardship.
- Assisting with data preparation, organization, documentation, and governance for AI, archive, language, and research-creation projects, with particular attention to Indigenous data sovereignty and community accountability.
- Providing technical and creative expertise for interdisciplinary research-creation projects involving AI, XR/VR, digital media, interactive installations, sensors, audio, video, 3D capture, and generative systems.
- Participating in research design, brainstorming, prototyping, documentation, writing, and knowledge mobilization for Pod and Lab initiatives.
- Taking leadership roles on new and ongoing AI research projects, including coordinating project tasks, supporting timelines, and helping move projects from concept through implementation.
- Mentoring and supporting undergraduate RAs working on related technical, creative, archival, language, and research-creation activities.
- Assisting with general project administration, research documentation, event planning, public presentations, workshops, and Haudenosaunee POD activities.
Qualifications
Education:
- Undergraduate degree in computer science or relevant area of focus
- Completion of, or working towards completion of, a Masters or Ph.D. degree would be considered an asset
Experience:
- 2 years of work experience supporting research in a related technical field or equivalent research experience
Skills, Abilities & Expertise:
- Advanced Computer Skills, including knowledge of coding in languages such as Python, JSON and C languages
- Intermediate Knowledge of AI/LLM research design
- Expertise with AI/LLM coding paradigms and methods
- Knowledge and expertise of code debugging
- Detail-oriented with an ability to function and process information with high levels of accuracy
- Ability to employ a systematic and efficient approach to work
- Personable and courteous in working relationships with colleagues, students and the public
- Ability to collect and analyze data in an objective manner
- Familiarity with regulations and guidelines governing research
- Familiarity with methods for research design, implementation, and analysis
- Familiarity with experimental design and analysis
- Ability to work independently and effectively as a member of the team to achieve lab/project goals
- Verbal and written communication skills with the ability to document technical information
