Summary
The Scalable Optimization, Learning, and Intelligent Decision-making (SOLID) Lab at the University of British Columbia (UBC) is seeking a highly motivated Postdoctoral Research Fellow to work on a funded research project focused on AI-enabled innovation for vanadium flow batteries (VFBs). This project aims to develop advanced AI and machine-learning methods for predicting battery degradation and accelerating the discovery of next-generation electrolyte and membrane materials, leveraging large-scale operational battery data.
Postdoctoral Research Fellow, AI-Enabled Innovation for Vanadium Flow Batteries (UBC Point Grey Campus, Vancouver)
Designation
Postdoctoral Research Fellow
Research Area
AI-enabled innovation for Vanadium Flow Batteries (VFBs), Machine Learning, Deep Learning, Time-series Modelling, Physics-informed AI, Explainable AI, Generative AI, Active Learning, Multi-objective Optimization, Battery Materials Discovery, Large-scale Industrial Data Analytics.
Location
UBC Point Grey Campus, Vancouver, British Columbia, Canada
Eligibility/Qualification
Required Qualifications:
- PhD (or close to completion) in Chemical Engineering, Electrical Engineering, Mechanical Engineering, Computer Science, Applied Mathematics, Materials Engineering, or a closely related field.
- Strong experience in one or more of the following areas:
- Machine learning and deep learning
- Time-series modelling
- Physics-informed or hybrid modelling
- Optimization and active learning
- Battery modelling and battery degradation
- Computational materials discovery
- Large-scale industrial data analytics
- Strong programming skills, particularly in Python.
- Strong publication record.
- Good written and oral communication skills.
- Ability to conduct independent research and work effectively in an interdisciplinary environment.
Desirable Qualifications:
- Experience with PyTorch, TensorFlow, scientific computing, or large-scale data processing.
- Prior experience in batteries or electrochemistry.
Job Description
The successful candidate will contribute to research in the following areas:
- Machine learning and data analytics for battery degradation prediction.
- Physics-informed and hybrid machine-learning models.
- Time-series modelling using deep learning and transformer architectures.
- Explainable AI for identifying factors affecting battery degradation and lifetime.
- Generative AI, active learning, and multi-objective optimization for battery materials discovery.
- Integration of field, simulation, and experimental data for model development and validation.
This project offers the opportunity to work with large-scale industrial battery datasets to understand degradation behavior, optimize operating strategies, and explore active learning and generative AI for materials development.
How to Apply
Interested candidates should email Professor Yankai Cao at yankai.cao@ubc.ca with the subject line “Postdoctoral Application – AI for Vanadium Flow Batteries.”
Please include the following documents:
- A Curriculum Vitae (CV).
- A brief cover letter describing your research background and interest in the position.
- Contact information for 2–3 references.
Last Date for Apply
Applications will be reviewed as they are received until the position is filled. The anticipated start date is April 1, 2027.
Apply Link
Email applications to yankai.cao@ubc.ca
Salary Ranges
The salary for this position is CAD $70,000 per year plus approximately 20% in benefits. Candidates who hold external postdoctoral awards or fellowships (e.g., an NSERC Postdoctoral Fellowship) will receive an additional top-up.
