PhD and postdoctoral opportunities are available in the areas of machine learning, AI safety, and AI governance at the University of Toronto, under the supervision of Assistant Professor Tim G. J. Rudner. The research group is affiliated with the Vector Institute for Artificial Intelligence and the Schwartz Reisman Institute for Technology and Society. Research interests include developing robust and transparent machine learning models for safety-critical and high-stakes settings, expanding the statistical foundations of generative models, reliable uncertainty quantification, interpretability, trustworthy AI agents, and regulatory approaches for frontier AI models. Tim G. J. Rudner is an incoming Assistant Professor of Statistical Sciences and Computer Science at the University of Toronto, with appointments at the Vector Institute. He holds a PhD in Computer Science from the University of Oxford and has received multiple prestigious awards and grants, including a $700,000 Foundational Research Grant and a $30,000 Apple Seed Grant. The group has published notable papers in top conferences such as AISTATS, EMNLP, ICML, and NAACL, focusing on uncertainty-aware priors, calibration in large language models, and robustness to subpopulation shifts. The lab is committed to supporting first-generation and low-income students, offering mentorship and guidance for navigating higher education. Applicants should have a strong background in machine learning, computer science, statistics, or related fields, with experience in AI safety, generative models, uncertainty quantification, or AI governance being highly desirable. The application window is open for positions starting in Fall 2026, with a deadline of December 28, 2025. For further details and to apply, candidates should visit timrudner.com and contact Tim G. J. Rudner via email or the website form. The University of Toronto offers a vibrant research environment in collaboration with leading AI institutes, providing opportunities to work on cutting-edge topics in machine learning and AI governance.