Funded MASc Position in Robotic Water-sampling

The University of British Columbia (UBC); Canada; On-site; CAD 43,000 - 56,000; Full time

Job summary

A leading Canadian university is seeking candidates for a funded PhD position focused on autonomous robotic water-quality sampling. This role involves developing a drone-based platform for rapid data acquisition and working alongside coastal communities to enhance climate resiliency. Ideal candidates will have a background in engineering with strong communication skills and a passion for interdisciplinary collaboration.

Qualifications

• Background in Robotics and/or Aerospace engineering is helpful but not required.
• Some coursework/project experience in optimization, machine learning, control systems, or robotics is desirable.
• Willingness to learn within an interdisciplinary team.

Responsibilities

• Develop a drone-based platform for rapid acquisition of in-situ water data.
• Co-develop the platform with coastal communities to improve resiliency.
• Use multiple robots to autonomously gather and transmit real-time data.

Skills

Interpersonal skills

Communication skills

Optimization

Machine learning

Control systems

Robotics

Education

Bachelor’s or Master’s degree in engineering

Job description

The University of British Columbia (UBC) is seeking a candidate for a funded MASc/PhD position in autonomous robotic water-quality sampling.

Offer Description

We have funded MASc/PhD positions available in autonomous robotic water-quality sampling at the University of British Columbia in Vancouver, Canada.

• We are developing a drone-based platform for rapid acquisition of in-situ water data at scale.
• We are working closely with coastal communities to co-develop this platform and improve resiliency to climate events.
• Multiple robots will autonomously gather and transmit data real-time over a cellular network to be processed and displayed on a custom cloud platform.

This position is part of the CLEAR project in collaboration with Rogers and the Bamfield Marine Sciences Centre and will include algorithmic, computational, and applied aspects.

About the Lab

This is a joint position between the research groups of Dr. Adrien Desjardins and Dr. Dominic Liao-McPherson. We also collaborate closely with Dr. Philippe Tortell in the Department of Earth and Ocean Sciences.

We are hosted within the Departments of Mechanical and Electrical & Computer Engineering on UBC's 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. UBC 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)

• Background in Robotics and/or Aerospace engineering is helpful but not required
• Strong interpersonal and communication skills
• Some coursework/project experience in optimization, machine learning, control systems, or robotics is desirable.
• No other specific qualifications beyond and a willingness to learn within an interdisciplinary team.

Application Instructions

Submit the following documents by email at dliaomcp {at} mech.ubc.ca and adrien.desjardins {at} ubc.ca

• A resume/CV;
• A cover letter/statement of intent (including relevant experience, your research interests);

Please submit all documents as a single .pdf file and use the following format for the email subject line: [CLEAR application]: LastName, FirstName

Key Dates

• November 10th 2025 | First review date for applications
• January 15th 2026 | Last review date for applications (no applications will be considered after this date)

Salary Ranges

A minimum yearly stipend of $40,000 for PhD students and $31,000 for MASc students.

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

Income from TA positions stacks on top

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+.