Associate Professor/Professor in Data Science Computation University of Toronto
· Department of Statistical Sciences About This Chance The University of Toronto's Department of Statistical Sciences seeks an Associate Professor or Professor whose research advances the theoretical and methodological foundations of computation in data science, including scalable algorithms, simulation, optimization and computational inference. This senior tenure-stream search focuses on the computational foundations of modern data science rather than on a single application domain. The department is seeking established scholars working on areas such as sampling and simulation, computational inference, optimization, randomized numerical methods and scalable algorithms for high-dimensional problems. Particular emphasis is placed on the statistical-computational tradeoffs behind these methods, including complexity, convergence and theoretical guarantees. Candidates must have an established international reputation and a sustained record of high-impact research and teaching. The successful appointee will be expected to lead independent research at the highest international level, maintain a competitive externally funded program, and carry teaching and service responsibilities in the Department of Statistical Sciences.



The position therefore combines senior research leadership with methodological depth across statistics, computer science and data science. data science computation computational statistics simulation optimization randomized numerical methods scalable algorithms high-dimensional problems Level Researcher Time Commitment Full-time Start Date Jul 1, 2027 Duration Full-time tenure-stream appointment at Associate Professor or Professor rank Reference Code 50282 / AJO #32804 Field Data Science Computation Specialization Statistics & Operational Research Organization Type University Funding & Compensation Amount Paid Funding Type Salary Funding Status Paid Period Per Year Requirements Education PhD in Statistics, Computer Science, Data Science or a closely related discipline by the time of appointment. Experience Established international reputation and a sustained record of research and teaching excellence in Data Science Computation or adjacent fields, evidenced by high-impact contributions and publications, major presentations, awards or other disciplinary leadership. Technical Skills Sampling and simulation Computational inference Optimization Randomized numerical methods Scalable algorithms High-dimensional computation Complexity analysis Convergence analysis General Skills Research leadership University teaching Academic service Scientific communication

📌 Associate Professor/Professor in Data Science Computation (Toronto)
🏢 Laplace Expert
📍 Toronto