PhD Position – Cooperative Autonomous Systems: The Networked Optimization, Diagnosis & Estimation (NODE) Lab at the University of Alberta’s Department of Mechanical Engineering is inviting applications for a Ph.D. position in Learning-Based Control for Cooperative Autonomous Systems interacting with Humans. The successful candidate will work under the supervision of Dr. Ehsan Hashemi and contribute to a large-scale interdisciplinary research program focusing on explainable AI, safe Reinforcement Learning, and cognitive-based control for autonomous robots. This position offers a unique opportunity to engage in cutting-edge research and collaborate with international partners.
|Research Area||Learning-Based Control for Cooperative Autonomous Systems|
|Location||University of Alberta, Edmonton, Canada|
|Eligibility/Qualification||Master of Science (or Engineering) degree in Electrical Engineering, Mechanical Engineering, Computer Science, Mathematics, or Engineering Physics|
|Job Description||See below|
|How to Apply||Email application to email@example.com with the subject “Application for PhD_NF23”|
|Last Date for Apply||December 01, 2023|
PhD Position – Learning-Based Control for Cooperative Autonomous Systems
- Develop learning-based control and distributed state estimation frameworks for autonomous robots interacting with humans in dynamic environments.
- Utilize explainable AI, safe Reinforcement Learning, and cognitive-based control for perception, navigation, and robust motion planning.
- Collaborate with research partners at McGill University, University of Michigan (Ann Arbor), and ETD Royal Institute of Technology (Sweden).
- Conduct experiments, theoretical/practical analysis, and mentor undergraduate and Master’s students.
- Contribute to publications in peer-reviewed journals and international conferences.
- Participate in activities related to Equity, Diversity, and Inclusion both within the lab and at the institutional level.
- Master of Science (or Engineering) degree in relevant disciplines.
- Interest and/or experience in SLAM, hybrid systems, learning-based control, and Reinforcement Learning.
- Programming skills for embedded systems, ROS, and coding in Python/C++.
- Ability to work independently.
- Effective written and verbal communication skills (proficiency in English and/or French).
Application Procedure: Interested candidates should submit the following documents in a single PDF file to firstname.lastname@example.org with the subject “Application for PhD_NF23” by December 01, 2023:
- Cover letter detailing related research experience and contributions to the interdisciplinary project.
- CV highlighting academic/professional achievements, publications, honors, awards, presentations, research collaborations, contributions to Equity, Diversity, and Inclusion, and a list of three professional references.
- Graduate and undergraduate transcripts.
- Score sheets for a test of English as a second language (if applicable).
- Copies of three relevant publications in control and estimation theory, robotics, mechanical/control systems, or human perception.
Deadline: Applications will be reviewed on an ongoing basis until 01 December 2023. Only shortlisted candidates will be contacted for interviews.