Research Associate (Lead Scientist - Turnkey Systems)

Job Title: Research Associate (Lead Scientist - Turnkey Systems) Company: University of Regina Job Category: Machine Learning Roles & Responsibilities: 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). * 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. * 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. * 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. * Familiarity with MLOps practices for continuous integration, deployment, and monitoring of machine learning models in production environments. 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. Work Location: Regina, Sikkim, Canada Availability: Full time

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\. Position Requirements Required Qualifications: * Master’s or PhD degree in Electrical Engineering, Computer Engineering, Mechatronics, Electronics Engineering, Computer Science, or a closely related field. * Proficiency in CAD software including AutoCAD, Fusion 360, and SolidWorks for mechanical design and system integration. * Proven experience managing project budgets, procurement processes, vendor relationships, and deliverable tracking for funded research or product\-development projects. Preferred Qualifications: * Experience with Altium Designer for high\-speed, multilayer PCB layout and signal integrity analysis. * 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 with cloud\-based AI/ML services (AWS SageMaker, Azure ML, Google Cloud AI) for scalable data processing and model deployment. Conditions of Employment: * Able to comply with applicable University policies, research\-security requirements, export controls, laboratory safety requirements, and confidentiality obligations. 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 – robyn.fahlman@uregina.ca Key Skills: Machine Learning, Python, TensorFlow Salary: Not disclosed