Funded PhD Positions in Multi-agent Optimization and Control

I have up to two funded PhD positions available in the Algorithms Optimization and Control Lab (AOCL) at the University of British Columbia in Vancouver, Canada.  

• Control and Optimization of Multi-agent Energy Systems: Our society is underpinned by the energy grid which must undergo unprecedented change over the coming decades if we are to meet net-zero emissions targets. This project seeks to develop distributed real-time optimization and control methodologies that are capable of coordinating large numbers of independent entities within our energy system (e.g., smart homes/buildings, power producers, electric cars, storage operators etc.) to operate the grid safely and efficiently.
• Multi-agent Construction Robotics: Many modern applications require robots to interact with others in unstructured environments. This project seeks to develop methodological and algorithmic frameworks based on optimization, control, and game-theory to enable multiple robots and humans to complete collaborative tasks, with a specific focus on safe interations, and robotic inspection on construction sites.

These projects have theoretical, computational, and applied aspects, they can be investigated in different ratios according to the interests of the researcher.

About the Lab

The AOCL works broadly at the intersection of control, optimization, and computing. We apply control, optimization, game-theory and machine learning to solve problems in energy, manufacturing, robotics, and aerospace.

We are hosted within the Department of Mechanical Engineering on UBCs Point Grey campus on the unceded lands of the xʷməθkʷəy̓əm (Musqueam) people, surrounded by forest, ocean and mountains. Vancouver is consistently ranked as one of the most diverse cities in Canada, and one of the most livable cities in the world. The lab offers a friendly and stimulating environment and the opportunity to become an expert in control, optimization, and computing while solving meaningful engineering problems.

Qualifications

• A Bachelor’s or Master’s degree in engineering (or a related field)
• Strong interpersonal and communication skills
• An introductory undergraduate control course
• Coursework/project experience in optimization and numerical computing is helpful but not required.
• No other specific qualifications beyond and a willingness to learn.

If you have any questions

If you’re interested in pursuing graduate school in beautiful Vancouver and any of this seems interesting to you, please don't hesitate to reach out.

Dominic Liao-McPherson | dliaomcp {at} mech.ubc.ca | https://mech.ubc.ca/dominic-liao-mcpherson/

How to apply

• Submit the following documents by email at dliaomcp {at} mech.ubc.ca.
• A resume/CV;
• A cover letter/statement of intent (including relevant experience, your research interests, and how they relate to the activities of the AOCL);
• Unofficial transcripts;
• Please submit all documents as a single .pdf file and use the following format for the email subject line: [AOCL application]: LastName, FirstName
• Those shortlisted for further consideration will be contacted for an online interview and given instructions about submitting a formal application to the Department of Mechanical Engineering.
• Due to the volume of emails received only those shortlisted will be contacted; I apologize in advance.

We encourage applications from members of groups that have been historically disadvantaged and marginalized, including First Nations, Métis and Inuit peoples, Indigenous peoples of North America, Black-identified persons, other racialized persons, persons with disabilities, and those who identify as women and/or 2SLGBTQ+.

Key Dates

• November 10th 2023  | First review date for applications
• January 15th 2024        | Last review date for applications (no applications will be considered after this date)

Funding Ranges

A minimum yearly stipend of $31,000 for PhD students and $27,500 for MASc students.

Award holders (e.g., CGS-M, UBC internal fellowship) will receive a top up.