🌍 Open PhD/MCS Position in Physics-Informed AI for Maritime Mobility

Research Area

Maritime mobility plays a critical role in global trade, transportation systems, and environmental management. However, current trajectory forecasting models often fail to account for the dynamic interactions between vessels and their surrounding environment, such as ocean currents and atmospheric conditions. This gap limits the reliability of predictions in complex maritime contexts.

The project, “Towards Optimized Mobility Forecasting Models with (Geo)Physics-Informed Machine Learning,” aims to address these challenges by integrating geophysical principles into machine learning models. Using Canadian maritime mobility data, the research will develop advanced methods such as physics-informed neural networks (PINNs) and graph-based representations to deliver accurate and explainable predictions for vessel trajectories.

The selected doctoral student will focus on developing and implementing these novel models, contributing to foundational advancements in maritime mobility research. The work has practical implications for safer navigation, environmental conservation, and maritime traffic management.

Position Details

The Faculty of Computer Science at Dalhousie University invites applications for a funded PhD or self-funded MCS position under the supervision of Prof. Gabriel Spadon. The successful candidate will join a multidisciplinary team working on physics-informed machine learning with a focus on maritime mobility forecasting.

The PhD student will receive funding and be enrolled in the Computer Science PhD program at Dalhousie University in Halifax, Nova Scotia, Canada. As part of the project, the candidate will have opportunities for international collaboration with researchers from the University of São Paulo (ICMC USP) and access to resources for presenting research findings at conferences and workshops.

Qualifications

We encourage applications from candidates with diverse backgrounds and skill sets. The ideal candidate will meet the following criteria:

• 📌 Holds a Master’s degree in Computer Science, Data Science, or a closely related field
• 📌 Strong academic performance and research aptitude
• 📌 Proficiency in programming, especially in Python, with experience in machine learning frameworks (e.g., TensorFlow, PyTorch)
• 📌 Interest or experience in physics-informed AI, geoinformatics, or maritime mobility
• 📌 Familiarity with spatiotemporal modeling, trajectory forecasting, or graph-based techniques is a plus
• 📌 Excellent written and verbal communication skills in English (IELTS 7 or equivalent preferred)
• 📌 Works well independently and as part of a collaborative research team

Candidates who are eager to learn and contribute to cutting-edge research are encouraged to apply, even if they do not meet all the above criteria.

Application Process

Interested candidates should submit the following documents by email to Prof. Gabriel Spadon (spadon@dal.ca) with the subject line “PhD Application - Fall #2025”:

• A detailed curriculum vitae
• A statement of purpose describing research interests and relevant experience
• Academic transcripts (undergraduate and graduate)
• Contact information for two referees

The deadline for applications is May 31, 2025, or until the position is filled.

Shortlisted candidates will be contacted for an interview by June 31, 2025.