OverviewPriority may be given to designated employment equity groups: women, Indigenous Peoples (First Nations, Inuit and Métis), persons with disabilities and racialized persons. Candidates are asked to self-declare when applying. Language requirements: English. Location: Mississauga. Tenure: Term. Duration: Until 31 March 2027. Work arrangements: due to the nature of the work, this position may be eligible for a limited hybrid work arrangement (onsite and telework).The RoleWe are seeking a Research Officer (RO) with expertise in artificial intelligence integration and the development of diverse tools utilizing reinforcement learning, deep learning, and Bayesian approaches. This role supports accelerated discovery, design, and development of novel clean energy and energy storage materials. The successful candidate will join the new Research Facility at the Clean Energy Innovation Research Centre in Mississauga. Core values: Integrity, Excellence, Respect, Creativity.You will work in a team with researchers and technical experts to advance research through a data management framework within theoretical, experimental, and material discovery workflows of self-driving laboratories. You will collaborate with leaders in accelerated material discovery and subject matter experts to implement AI integration strategies for tracking, integration, and management of tools in research laboratories. Responsibilities include data collection and validation, database architecture design, and deployment of advanced tools. You will investigate and develop AI-enabled digital frameworks and architectures to address objectives in materials science at CEI-Mississauga. You will lead or partner with software developers to optimize data infrastructure for advanced data analytics and machine learning.You will participate in developing new research proposals, managing projects, maintaining partnerships with external academic, industrial and government collaborators,



and supervising junior staff, students and vendors. This dynamic role requires initiative in an evolving R&D environment and input into direction and priorities of the initiative in Mississauga.Screening CriteriaApplicants must demonstrate they meet the following criteria to be considered:Education:Ph.D. in Chemistry, Physics, Computer Science, Engineering, or similar domain. Degree equivalency information for certificates and diplomas issued abroad is available.Experience:Proven experience in integrating AI/ML solutions in research or laboratory environments for materials science or process optimization.Proven experience in robotic learning for materials science, including automating data extraction and analysis in mineral processing or energy storage applications.Experience with development and implementation of AI/ML tools (reinforcement learning, deep learning, Bayesian methodologies).Experience with large/multi-format databases, including data handling and organization.Significant experience using Python (numpy, scipy, pandas, etc.).Robust publication record in high-impact journals.Experience defined as within the last 1–3 years; significant experience as 3–5 years or more.Assets:Experience with data lineage/tracking in materials science and software development focused on AI applications, collaborating with or leading software development efforts in data analytics, machine learning, and version control systems.Condition of Employment:Reliability Status.



Verification of background information over the past 5 years is required.Technical and Behavioral CompetenciesTechnical competencies in AI/ML frameworks (TensorFlow, PyTorch, Keras) including reinforcement learning, deep learning and Bayesian modeling.Proficiency in Python and frontend/backend frameworks (e.G., Django, Node.Js, React, Angular).Knowledge of clean energy technologies; data integration pipelines via APIs, ETL, real-time processing; scalable AI-driven dataenvironments.Proficiency with GitHub/GitLab for code management and collaborative development.Understanding of FAIR data principles and their application in AI/data science research.Experience deploying AI/data science applications in Linux environments and HPC/Cloud for large-scale processing.Behavioural competencies:Research - Communication (Level 2); Self-knowledgement/self-development (Level 2); Creative thinking(Level 3); Teamwork (Level 2); Results orientation (Level 3).Compensation and BenefitsThe position is at the AsRO/AcRO level, mid-career, with salary range $83,985 to $139,608. Salary may be determined based on expertise and prior outcomes/impacts. Benefits include a robust pension plan, health and dental coverage, disability and life insurance, and other well-being supports. Additional notes on salary levels and progression are provided in the original description.Notes:Relocation assistance may be provided; a pre-qualified list may be established for similar positions for one year; preference to Canadian citizens and permanent residents. The incumbent must adhere to safe workplace practices. Applications from term or continuing NRC employees should use the SuccessFactors Careers module from an NRC computer.ClosingClosing Date: 11 May 2026 - 23:59 Eastern Time. For questions, cite requisition number 24671. Email: [email protected]. Telephone: (phone hidden).#J-18808-Ljbffr

📌 Ai/Ml Research Officer - Materials & Process Optimization - C$83,985 - C$139,608 A Year (Winnipeg)
🏢 Clean Energy Innovation Research Centre
📍 Winnipeg