Job ID
75595
Job Title
RESEARCH ASSOCIATE (I)
Regular/Temporary
Regular
Location
McMaster Innovation Park (MIP)
Open Date
2026/05/06
Job Type
Limited Term (>12 months)
Close Date
2026/05/15
Employee Group
Unifor Unit 1, Staff
Favorite Job
Department
Inst for Research on Aging
Full/Part Time
Full-Time
Salary Grade/Band
Grade 12
Salary Range
$46.04 - $64.75 (hourly)
Job Code
JD0550
Existing Vacancy
Yes - Newly Created Position
Contract Duration
13.1 Months
Target Number of Openings
1
Hours per Week
35
Posting Details
Schedule
Monday - Friday, 8:30am - 4:30am, 60 minutes unpaid lunch, 35 hours per week
Education Level
Doctoral degree in a relevant field of study.
Career Level
Requires a minimum of 7 years of relevant experience.
Anticipated Fill date
June 1, 2026
Job Description
Description:
The McMaster Institute for Research on Aging (MIRA) houses CANWEAR (Canadian Wearables Research Hub). CANWEAR is a national core research facility, collaborating with with partners across Canada (University of Western Ontario, UBC) that accelerates high-quality, reproducible wearable and remote monitoring research to support health and mobility across the adult life course. CANWEAR provides standardized, validated, and device-agnostic analytics to support the integration of wearable-derived mobility and activity measures across McMaster’s research programs and external cohorts. CANWEAR enhances the scientific value and comparability of digital measures by reducing reliance on proprietary algorithms and enabling transparent, scalable data pipelines. The hub also serves as a national platform for methodological innovation, training, and interdisciplinary collaboration in wearable data science.
CANWEAR is seeking a Research Associate that will work closely with its Director and affiliated researchers to deliver its mission through integrated core activities that address the full wearable research lifecycle: 1) Wearable device evaluation; developing standardized criteria for data acquisition, sensor selection, and study design, and evaluation and validation of existing and emerging wearable technologies for research suitability, 2) Analytics development and implementation: providing access to validated, device-agnostic, open-source analytics and data pipelines that ensure transparency, reproducibility, and comparability of wearable-derived measures across studies and populations. 3) Development and integration of novel analytic methods, including advanced statistical and AI-enabled approaches, into the open-source platform. This position will report to Dr. Beauchamp, Director CANWEAR.
Job Summary:
Responsible for planning, managing, and overseeing a large, multi-site, multi-disciplinary research program, with the potential to compose, lead, and conduct research as an independent investigator or as a co-investigator within a faculty member's program. Develops collaborations and partnerships with research user groups to help shape research directions and ensure effective research transfer.
Purpose and Key Functions:
Supervision:
- Provide lead hand supervision and is responsible for the quality and quantity of work of others.
- Ongoing responsibility for supervising up to 9 casual employees at any one time.
Requirements:
- Doctoral degree in a relevant field of study.
- Requires 7 years of relevant experience.
Assets:
Required:
This role requires expertise in multi-sensor wearable technology processing and pipeline development within a research setting. The ideal candidate brings 5+ years of professional experience in Python, with strong skills in version control and package management using Git, GitHub, and PyPI, and a proven ability to lead complex software development projects, including managing timelines, resources, and sub-projects. They have extensive experience working with large datasets (NumPy, Pandas, Matplotlib), handling binary data, and using SQL for relational databases. A deep technical understanding of wearable biosensor systems is essential, including device evaluation, sensor calibration, data quality assessment, sensor fusion, and feature extraction across time and frequency domains, with specific experience in accelerometer, gyroscope, ECG, PPG, and GPS data. The candidate should also have knowledge of clinical outcomes related to mobility and health in aging populations (e.g., gait, sleep, physical activity, cognition, posture) and demonstrated experience applying wearable technologies across all stages of research, from study design through to analysis, interpretation, and publication.
Additional assets desired:
Proficiency in R, Matlab, C# - Familiarity with the European Data Format (EDF) for storing standardized time-series dataPrevious experience related to the development of standards for the use of wearable devices to measure health and mobility outcomes in aging populations. -Experience developing and validating novel techniques for deriving real-world health and mobility outcomes form wearable device data. - Experience participating in collaborative, interdisciplinary research (i.e., team science)
How To Apply
To apply for this job, please submit your application online.
Employment Equity Statement
McMaster University is located on the traditional territories of the Haudenosaunee and Mississauga Nations and within the lands protected by the “Dish With One Spoon” wampum agreement.
The diversity of our workforce is at the core of our innovation and creativity and strengthens our research and teaching excellence. In keeping with its Statement on Building an Inclusive Community with a Shared Purpose, McMaster University strives to embody the values of respect, collaboration and diversity, and has a strong commitment to employment equity.
The University seeks qualified candidates who share our commitment to equity and inclusion, who will contribute to the diversification of ideas and perspectives, and especially welcomes applications from indigenous (First Nations, Métis or Inuit) peoples, members of racialized communities, persons with disabilities, women, and persons who identify as 2SLGBTQ+.
As part of McMaster’s commitment, all applicants are invited to complete a confidential Applicant Diversity Survey through the online application submission process. The Survey questionnaire requests voluntary self-identification in relation to equity-seeking groups that have historically faced and continue to face barriers in employment. Please refer to the Applicant Diversity Survey - Statement of Collection for additional information.
Job applicants requiring accommodation to participate in the hiring process should contact:
- Human Resources Service Centre at 905-525-9140 ext. 222-HR (22247), or
- Faculty of Health Sciences HR Office at ext. 22207, or
- School of Graduate Studies at ext. 23679
to communicate accommodation needs.
Hybrid Work Language
This position is a hybrid position that requires presence in the office some of the time.
AI Statement
McMaster and its third-party partners may use AI tools to screen, assess, or select applicants during the hiring process. Please note that currently our recruitment platform does not use AI nor is it part of our current recommended recruitment process.
