Research assistant – casual position
Start date: August 01, 2026
Application deadline: July 10, 2026
Term: August 01, 2026, to November 30, 2026
Supervisor: Dr. Daniel Chang
Faculty: Faculty of Humanities and Social Sciences
Overview:
Dr. Daniel Chang, Assistant Professor in Distance Education at Athabasca University and Director of the AI-EDU Research Lab, is seeking two graduate research assistants to support research in the lab. The project examines how post-secondary students use, evaluate, and disclose generative AI in coursework. The work draws on work in learning sciences and educational technology and connects to human-AI interaction, writing pedagogy, linguistic justice, and equitable teaching practice. Three casual RA positions are available. One general technical Research Assistant and two graduate level Research Assistants. The positions may be conducted remotely, subject to project needs and institutional requirements. This position is suitable for those who consider pursuing academic career in the future (i.e. doctoral degree).
Specific activities include, but are not limited to:
These positions will support AI-EDU Lab’s empirical and conceptual research on the use of generative AI. Specific research activities may include but not limited to:
- conducting literature searches and preparing annotated summaries;
- supporting research ethics applications, consent materials, recruitment documents, survey instruments, interview protocols, and project documentation;
- assisting with data organization, cleaning, and de-identification;
- assisting with secure data management, coding, and configurations (software & hardware)
- supporting qualitative coding and thematic analysis of student interviews, open-ended survey responses, and coursework-related reflections;
- supporting quantitative or mixed-methods analysis of survey and performance-related data, depending on the candidate’s background; AND/OR
- attend and contributing to research meetings, analytic memos, conference proposals, proceedings papers, manuscripts, and knowledge mobilization materials (i.e. website maintenance or updates).
The graduate level RAs will primarily support or lead literature review, research administration, data preparation, coding, analytic memos, and conference/manuscript preparation.
The general RA will support day-to-day technical operations of the AI-EDU lab, maintenance, and research management.
The successful candidates will work closely with the members of AI-EDU Lab (), and directly report to, Dr. Daniel Chang at Athabasca University. AI-EDU Lab is a team-focused dynamic, integral, fast-paced, efficient research team. We expect the candidates will be of the similar personal qualities. Evaluation of performance will be assessed near the contract ends. Renewal will be subject to budget and prior performance in the lab. Dr. Chang will provide directions and training for qualitative research, scholarly writing and quantitative research analytic skills necessary to complete the project.
Graduate-Level RA Qualifications:
- current enrolment in a graduate program in distance education, education, educational psychology, educational technology, TESOL, writing, human-computer interaction, applied linguistics, or a combination of related fields at Athabasca University or another eligible Canadian public post-secondary institution
- strong academic writing, communication, organization, time-management, confidentiality, and independent work skills
General-Level RA Qualifications
- completed or nearly completed BSc degree in science, computing science, or related discipline (or an equivalent combination of education, training and experience) with three years of experience deploying complex research software packages; OR
- completed or nearly completed BA degree (in any discipline) demonstrating sufficient experience deploying complex research software packages.
- Sufficient knowledge of deploying virtual machines and containers using OpenStack of VMware environments.
- Sufficient expertise in high-performance computing, network structure, cloud infrastructure, and software deployment.
Preferred qualifications for graduate level RAs:
- experience with literature reviews, citation management, and synthesis of peer-reviewed research;
- experience with qualitative methods, such as coding, thematic analysis, discourse analysis, or interview analysis;
- experience with quantitative or mixed-methods research, survey analysis, or tools such as R, SPSS, Jamovi, Excel, NVivo, ATLAS.ti, or Dedoose;
- familiarity with SRL theory, AI ethics, academic integrity, educational technology, writing pedagogy, TESOL, or equity-oriented research;
- prior experience preparing conference proposals, proceedings papers, manuscripts, research reports, or knowledge mobilization materials.
How to apply:
Qualified individuals are encouraged to submit their application by email to Dr. Daniel Chang at dchang@athabascau.ca AND info@aiedulab.ca . Applications should include, as a single PDF file:
- a brief cover letter summarizing your skills, research interests, relevant experience, and availability;
- a current academic curriculum vitae (CV);
- an unofficial copy of your transcript;
- a writing sample/or a publication;
- the contact information for 1-2 references.
Evaluation of applications will begin immediately and will continue until a suitable candidate is found. All applicants are thanked for their interest in this position; however, only candidates selected for an interview will be contacted. Athabasca University and the researchers are committed and seek to support equity in employment and research opportunities. We strongly encourage applications from Indigenous people, people of colour, people with disabilities, 2SLGBTQ+ people, women, and other historically marginalized groups. Applicants are welcome, but not required, to self‐identify in their letter of application. For more information on this Research Assistant Opportunity, please contact Dr. Daniel Chang, PhD at the coordinates below, on or before July 10th, 2026
Scope of work will be around 5-10 hours per week (approximate, based on workload) and may vary based upon activity. This position has a maximum of 130 hours.
Dr. Daniel Chang
Assistant Professor, Distance Education
Athabasca University
Director, AI-EDU Research Lab
E-mail: dchang@athabascau.ca
Website: aiedulab.ca