Vacancies

Research topics

• Learning: reinforcement learning, randomized algorithms

• Operations research: stochastic and robust programming, dynamic programming, optimization algorithms

• System theory: stochastic systems, optimal control, fault detection and estimation

• Applications: health-monitoring and control of large-scale and distributed engineering systems, including smart energy systems (e.g., electricity and water networks), high-tech systems (e.g., high-end printers and lithography machines), mobility and transportation (e.g., logistics and autonomous cars), and diagnosis in healthcare (e.g., epileptic seizures).

Openings

We currently have open PhD positions at the University of Toronto in the broad area of reinforcement learning. Our primary focus is on theoretical foundations, including both computational aspects (e.g., algorithm design) and statistical aspects (e.g., sample complexity).

We are looking for candidates with

• strong mathematical skills background in o Systems and Control, Operations Research, Computer Science, Electrical Engineering, or a related field;

• excellent command of the English language and communication skills.

Application

• Detailed CV including contact information of 1-2 references
  

• Academic transcripts of (under)graduate coursework for PhD applicants
  

• Brief description (1-2 paragraphs) about any prior research experience
  If you are interested, please submit your application or inquiries to P.MohajerinEsfahani@utoronto.ca.