Senior Research Associate, Civil Engineering – large-domain hydrological modelling

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Description

The Civil Engineering in the Schulich School of Engineering invites applications for a Senior Research Associate. This Full-time Fixed Term position is for approximately 34 months (based on length of grant funding), with the possibility of extension.

Reporting to the Principal Investigator, the candidate will conduct high quality research in the area of large-domain hydrological modelling. While the candidate will pursue independent research tasks, they will provide support through mentoring other graduates (MSc’s/PhD’s) of the PI’s Research Team.

The successful candidate will demonstrate a high level of research performance through effective sharing and discussions of ideas in a highly collaborative environment that includes industrial and government partners. The position of is a full-time appointment, 35 hours per week, Monday to Friday, 7 hours per day. Flexible work hours and remote working arrangements are possible in consultation with the PI.

Summary of Key Responsibilities (job functions include but are not limited to):

– Conduct studies that advance the science and practice of hydrological modeling
– Prepare drafts of papers and reports as necessary
– Should be able to mentor graduate students and junior colleagues as necessary
-Establishes and maintains effective, productive relationships with staff, peers, immediate supervisor and senior management and with the campus community.
-Manages own time effectively and ensures immediate reports to manager is kept informed of activities, and progress of work.
-Provide technical support for other team members through technical advice
-Recommend change to processes or procedures
-Must be open to learning and development, and be willing to accept new challenges and assignments.
-Lead the development and maintenance of integrated, community-driven hydrological modeling platforms for large-domain applications.”
-Develop and implement multi-agent AI systems and Large Language Model (LLM) workflows to automate scientific discovery and model configuration.
-Bridge the gap between research and operations (R2O) by integrating process-based models with operational frameworks
-Conduct large-scale spatio-temporal analysis of cold region hydrological processes and water resources using remote sensing and high-performance computing (HPC)
-Develop and deliver specialized curriculum on the application of Artificial Intelligence and Machine Learning in Hydrology.
-Provide support/materials for core undergraduate courses in Engineering Hydraulics and Hydrology.
-Provide technical expertise to government and intergovernmental bodies regarding environmental data standards and sustainability frameworks.

Qualifications / Requirements:

-The incumbent should have a Ph.D. degree and at least two years of postdoctoral experience in the research area of large-domain hydrologic modeling.
-In-depth knowledge of hydrological and water resources principles, modelling, and forecasting.
-Proven research track record or potential for scholarly research in continental domain hydrological prediction.
-Demonstrated expertise in developing reproducible, modular and scalable modeling workflows and working with large domain instantiations of the SUMMA modeling framework.
-Experience with ‘Physics-Informed Machine Learning’ and the development of autonomous AI agents for environmental decision support.
-Experience with large sample parameter estimation of modern physically based hydrological models at scale.
-Experience working across multiple countries/jurisdictions where cold region hydrological processes are critically important.
-Evidence of a contribution to research, including successful external grant applications.

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