We are hiring talented PostDoc candidates
NODE Lab invites applications and queries for a PostDoc position for: Risk-Aware Controls for Multi-Agent Autonomous Systems. This Postdoc researchers in control, machine learning, autonomous navigation, and cognitive neuroscience for a large-scale interdisciplinary research program. In this Postdoc research position, learning-aided control and risk-aware navigation frameworks will be developed for multi-agent autonomous systems cooperating/interacting with humans in dynamic environments. In this regard, safe Reinforcement Learning (and Bayesian optimization), and cognitive based control will be used for perception, motion planning, and robust control of autonomous systems.Â
Benefits of working with us
This project will involve collaboration with research partners at McGill University, University of Michigan (Ann Arbor), and KTH Royal Institute of Technology (Sweden); some national and international travel may be required. This position is available to Canadian citizens, permanent residents of Canada, refugees in Canada, and international applicants.
Your skills
Completion of PhD degree in Computer Science, Electrical Engineering, Mechanical Engineering, Mathematics, and Cognitive Neuroscience (interdisciplinary PhD research are preferred)
Keen interest and/or experience (coursework, research, and/or industrial) in: RL, reachability analysis, hybrid systems, adaptive control, and cognitive neuroscience
Programming for embedded systems, ROS, and coding in Python/C++
Proven ability to work independently
Effective written and verbal communication skills (proficiency in English and/or French).
Deadline
Feb. 01, 2025
Additional details
This position has also been posted here
We are hiring talented PhD candidates
NODE Lab invites applications and queries for a PhD position for: Learning-Based Control for Cooperative Autonomous Systems Interacting with Humans. This PhD position will be open to highly-qualified and outstanding researchers in control, machine learning, autonomous navigation, and perception for a large-scale interdisciplinary research program. In this PhD research, learning-based control and distributed state estimation frameworks will be developed for autonomous robots cooperating and interacting with humans in dynamic environments. In this regard, explainable AI, safe Reinforcement Learning (and Bayesian optimization), and cognitive based control will be used for perception, navigation, and robust motion planning of autonomous systems (with applications to assistive devices and networked robots).
Benefits of working with us
This project will involve collaboration with research partners at McGill University, University of Michigan (Ann Arbor), and KTH Royal Institute of Technology (Sweden); some national and international travel may be required. This position is available to Canadian citizens, permanent residents of Canada, refugees in Canada, and international applicants.
Your skills
Completion of Master of Science (or Engineering) degree in Electrical Engineering, Mechanical Engineering, Computer Science, Mathematics, or Engineering Physics
Keen interest and/or experience (coursework, research, and/or industrial) in: SLAM, hybrid systems, learning based control, and Reinforcement Learning
Programming for embedded systems, ROS, and coding in Python/C++
Proven ability to work independently
Effective written and verbal communication skills (proficiency in English and/or French).
Deadline
15th October
Additional details
This position has also been posted here.