Engage in a funded 3.5-year PhD project aiming to enhance calibration methodologies for particle simulations, leveraging AI and machine learning technologies. Enjoy annual tax-free stipends and full tuition coverage.

This PhD opportunity commences in October 2026 and focuses on addressing the challenges of selecting and parameterising contact models in particulate continuum models. Through the integration of advanced AI techniques, participants will work on developing robust calibration strategies. The project incorporates emerging methodologies including machine learning for parameter optimisation, model selection, and uncertainty quantification, ensuring impactful research outcomes.

Key Responsibilities:



• Investigate calibration problems in particulate models • Formulate methodologies integrating machine learning • Perform data analysis using deep learning methods • Collaborate on developing productive calibration protocols • Employ surrogate modelling to mitigate computational costs

Requirements: • At least a 2.1 honours degree or master’s equivalent • Relevant background in science or engineering disciplines • Proficiency in AI and machine learning concepts • Eagerness to begin in October 2026 • Strong analytical skills and research aptitude

This PhD studentship offers an exciting chance to contribute significantly to AI-enhanced calibration strategies.

📌 PhD in Calibration with AI Innovations (Winnipeg)
🏢 Emerging Scholars Council
📍 Winnipeg