Research Associate (Lead Scientist - Turnkey Systems)

Research Associate (Lead Scientist - Turnkey Systems)

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Please see Special Instructions for more details.

Interested candidates are invited to send their applications using the online portal. Please submit the following documents:

• Cover letter
• Curriculum vitae – including a list of publications, technical skills, and laboratory techniques mastered
• Research statement (1‑2 pages) – describing your past contributions and future research vision in development of Turnkey systems and sensing
• Names and contact information of two professional referees (at least one familiar with your hands‑on laboratory work)

For questions, please email [email protected]

All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.

Applicants must be legally entitled to work in Canada, and the work associated with this position must be performed within Canada.

Position Details

Posting Summary

Competition Number	20260173A/S
Position Title	Research Associate (Lead Scientist - Turnkey Systems)
Faculty/Department	Faculty of Engineering and Applied Science
Unit	Engineering-Dean's Office
Employee Group	CUPE 5791 - Research
Collective Agreement Consideration	Open to the Public.
CUPE 5791 Job Family	Research
Category	Staff
Number of Vacancies	1
Position Summary	The University of Regina is a public research university with a strong commitment to interdisciplinary scholarship, graduate education, and research that engages local, national, and global challenges. Located in Regina, Saskatchewan, the University is situated in a mid-sized and increasingly diverse city in the Canadian prairies. The University is situated on Treaty 4 Territory—the territories of the Nêhiyawak, Anihšinapek, Dakota, Lakota, and Nakoda peoples—and the traditional homeland of the Métis/Michif Nation, with a presence in Treaty 6. The position will focus on designing, developing, and integrating turnkey sensing systems across the full electronics and mechanical lifecycle—from multilayer PCB design and microcontroller programming to graphical user interface (GUI) development and mechanical CAD modelling (AutoCAD, Fusion 360, SolidWorks). The role involves system-level integration of IoT connectivity, embedded systems, and diverse AI/ML techniques for sensor platforms, while also sitting at the core of mechatronics and swarm systems engineering for UAVs and drones operating across air, land, and water, including unmanned aerial, ground, surface, and amphibious/aerial-aquatic platforms. Responsibilities encompass mechatronic subsystem design—actuation, propulsion, control, power, and sealing/waterproofing—as well as swarm design—formation control, task allocation, decentralized autonomy, inter-agent communication, and collaborative sensing—alongside architecting scalable hardware/software stacks for individual and swarm operations across domains, developing multi-domain sensor suites such as LiDAR, cameras, IMU/GNSS, radar, sonar, and environmental/payload sensors, implementing AI/ML for perception, sensor fusion, SLAM, object tracking, path planning, and multi-agent decision-making, and building embedded/IoT stacks including microcontrollers, ROS/ROS2, MAVLink, MQTT, edge computing, and GUI dashboards. The engineer will also perform mechanical CAD, prototyping, waterproofing, buoyancy, thermal, and vibration validation for air, land, and water platforms, and manage project budgets, procurement, vendors, and deliverables for funded research projects.Responsibilities: You will be leading a dynamic team tof 3 engineers/technitions and students. Design and develop multilayer PCBs for sensor interfacing, signal conditioning, data acquisition, and power management using industry-standard EDA tools (e.g., Altium, KiCad, Eagle). Program microcontrollers (ARM Cortex, ESP32, Arduino, PIC, or equivalent) in C/C++, Python, or MicroPython for real-time data acquisition, actuator control, communication protocols, and low-power operation. Develop intuitive graphical user interfaces (GUIs) using Qt, PyQt, LabVIEW, or web-based dashboards for real-time data visualization, remote system control, and end-user interaction. Lead system-level design integration, ensuring seamless interaction between sensing materials, analog front-ends, digital processing units, communication modules, and power subsystems. Create mechanical enclosures, mounting fixtures, and system housings using CAD software, including AutoCAD, Fusion 360, and SolidWorks, to protect electronic assemblies for field-deployable and ruggedized environments. Implement IoT connectivity (Wi-Fi, Bluetooth, LoRaWAN, Zigbee, cellular, MQTT, HTTP/REST) and integrate AI/ML algorithms for on-device sensor data processing, including: Edge AI: TensorFlow Lite Micro, CMSIS-NN, or similar frameworks for real-time inference on microcontrollers. Predictive Analytics: Time-series forecasting (LSTM, GRU, Prophet) for predictive maintenance and environmental trend analysis. Anomaly Detection: Isolation Forest, Autoencoders, or One-Class SVM for identifying outliers and sensor faults. Classification: Support Vector Machines (SVM), Random Forest, Gradient Boosting (XGBoost, LightGBM), and Neural Networks for pattern recognition and event detection. Regression Models: Linear/Polynomial Regression, Ridge, Lasso, and Gaussian Process Regression for sensor calibration and concentration prediction. Unsupervised Learning: K-Means, DBSCAN, and PCA for clustering and dimensionality reduction of high-dimensional sensor data. Reinforcement Learning: Application of RL for adaptive sensor control and optimization of system parameters. Deep Learning: CNNs for spectrogram/image analysis and RNNs/LSTMs for sequential data processing. Generative AI: GANs or VAEs for synthetic data generation to augment limited training datasets. Manage project budgets, track procurement processes, coordinate with external vendors and subcontractors, and ensure timely delivery of project milestones and deliverables for funded research initiatives. Conduct rigorous system testing, validation, troubleshooting, and iterative improvement of turnkey sensing platforms in both laboratory and field settings; document test results and performance metrics. Prepare comprehensive technical documentation, including schematics, bills of materials (BOMs), assembly drawings, wiring diagrams, user manuals, and test reports. Train and mentor students, junior technicians, and researchers in electronics design, system integration, soldering techniques, and testing procedures. Maintain laboratory inventory, electronic components stock, equipment calibration schedules, and safety compliance for electronics prototyping and fabrication workstations. Support technology demonstrations for academic researchers, industry representatives, government partners, and prospective commercialization stakeholders. Coordinate with external certification bodies and regulatory compliance officers as needed for product safety and electromagnetic compatibility (EMC) testing. Participate in out reach programs.
Position Requirements	Required Qualifications: Master’s or PhD degree in Electrical Engineering, Computer Engineering, Mechatronics, Electronics Engineering, Computer Science, or a closely related field. Minimum 2–3 years of hands-on experience in PCB design (multilayer, high-speed, mixed-signal), microcontroller programming, and GUI development for hardware systems. Proficiency in CAD software including AutoCAD, Fusion 360, and SolidWorks for mechanical design and system integration. Demonstrated knowledge of IoT connectivity protocols (e.g., MQTT, HTTP, BLE, LoRa, Wi-Fi) and embedded systems, with practical experience implementing one or more of the following AI/ML techniques: Edge AI frameworks (TensorFlow Lite, CMSIS-NN) Classification and regression models (Random Forest, SVM, XGBoost) Time-series analysis (LSTM, Prophet, ARIMA) Unsupervised learning (PCA, K-Means, Autoencoders) Anomaly detection algorithms Proven experience managing project budgets, procurement processes, vendor relationships, and deliverable tracking for funded research or product-development projects. Strong troubleshooting, analytical, and documentation skills, with the ability to work independently and collaboratively in a multidisciplinary research environment. Preferred Qualifications: Experience with Altium Designer for high-speed, multilayer PCB layout and signal integrity analysis. Familiarity with sensor integration (chemical, gas, environmental, or optical sensors) and analog front-end circuit design (op-amps, filters, ADCs). Experience with field deployments of electronic systems in outdoor or industrial environments, including ruggedized packaging and weatherproofing. Knowledge of product certification standards (FCC, IC, CE, UL) and quality assurance procedures. Experience working in a university research lab, startup, or product-development environment with a track record of translating prototypes to near-market systems. Proficiency in version control (Git) and collaborative software development practices. Experience with cloud-based AI/ML services (AWS SageMaker, Azure ML, Google Cloud AI) for scalable data processing and model deployment. Knowledge of model optimization techniques (pruning, quantization, knowledge distillation) for efficient deployment on resource-constrained edge devices. Familiarity with MLOps practices for continuous integration, deployment, and monitoring of machine learning models in production environments. Willingness to engage respectfully with Indigenous communities and partners, where relevant, under the guidance of University specialists. PhD Conversion Pathway: This position is designed for talented engineers and scientists who wish to combine cutting-edge turnkey systems development with advanced academic training. After an initial 6–12 month probationary period, high-performing candidates will be eligible to transition into a job-embedded PhD program, co-supervised by faculty in Electronic Systems Engineering. The PhD research will build directly on the incumbent’s work in IoT-enabled sensing systems, AI/ML, and PCB/system integration, allowing the candidate to earn a doctoral degree while remaining employed full-time at the University. Conditions of Employment: Able to comply with applicable University policies, research-security requirements, export controls, laboratory safety requirements, and confidentiality obligations. Willing and able to undertake fieldwork and work-related travel, as required. Must possess a valid driver’s license or willingness to acquire a drivers licence in 6 months of joining.
Physical Demands
Pay Grade	As Per CUPE 5791 Research
Salary Range	Amount or As Per CUPE 5791 Research
Status	Term
Work Hours
Duration (if Term/Temporary)	up to 8 years
Full-Time/Part-Time	Full Time
Preference Posting	No Preference
Target Posting	Not Targeted

Additional Information

Contact Information	Robyn Fahlman – [email protected]
Job Open Date	10/16/2026
Job Close Date	12/15/2026
Open Until Filled	No
Special Application Instructions	Interested candidates are invited to send their applications using the online portal. Please submit the following documents: Cover letter Curriculum vitae – including a list of publications, technical skills, and laboratory techniques mastered Research statement (1‑2 pages) – describing your past contributions and future research vision in development of Turnkey systems and sensing Names and contact information of two professional referees (at least one familiar with your hands‑on laboratory work) For questions, please email [email protected] All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority. Applicants must be legally entitled to work in Canada, and the work associated with this position must be performed within Canada.
Safety Statement	The University is committed to maintaining a safe and healthy workplace and strengthening a culture of safety across the campus community. All employees share responsibility for contributing to a safe working environment.
Diversity Statement	The University of Regina is committed to an inclusive workplace that reflects the richness of the community that we serve. The University welcomes applications from all qualified individuals, including individuals within the University’s employment equity categories of women, persons with disabilities, members of visible minorities, Indigenous persons, individuals of diverse gender and sexual orientation and all groups protected by The Saskatchewan Human Rights Code, 2018.

Supplemental Questions

Required fields are indicated with an asterisk (*).

Documents Required

Required Documents

1. Resume/Curriculum Vitae
2. Cover Letter
3. Reference Contact Info
4. Research Interests/Projects

Optional Documents