Postdoctoral Scholar in Forest & Yield

Position: Postdoctoral Scholar in Forest Growth & Yield
Job Overview  The University of Alberta's Post-Doctoral Fellows Association is appointing a Postdoctoral Scholar for a three‑year initial contract. This position focuses on developing next‑generation forest dynamics models for the Western Boreal and Rocky Mountain regions, integrating advances in remote sensing, and applying the models to operational forest management and timber supply analysis.
Location  In‑person at North Campus, Edmonton.
Benefits  Comprehensive benefits package is provided.
Responsibilities   Lead the critical evaluation, augmentation, and redevelopment of growth and yield/forest dynamics models, including testing alternative model architectures to better incorporate climate, succession, and silviculture effects.
Design and implement robust, reproducible workflows that integrate long‑term permanent sample plot data with remote sensing observations and other geospatial datasets.
Exercise high‑level independent judgment to advance the project from broad conceptualization through to validated, simulation‑ready model systems suitable for management applications.
Prepare technical reports, high‑impact peer‑reviewed publications, and knowledge‑transfer activities with government and industry partners.
Collaborate effectively with lab members and external partners while maintaining strong ownership of the modelling work.
Qualifications   PhD awarded within the last 5 years in Forestry, Forest Science, Quantitative Silviculture, Forest Biometrics, or a closely related field with a clear focus on growth and yield, stand dynamics, or quantitative forest modelling.
Demonstrated ability to build, validate, troubleshoot, and apply complex statistical or mathematical models to real forestry problems (examples: non‑linear mixed‑effects models, non‑parametric models, process‑based or hybrid models).
Strong evidence of independent research leadership – the ability to take a broad goal, break it into actionable technical steps, and drive progress with limited day‑to‑day supervision.
Proficiency in R and/or Python with a commitment to clean, well‑documented, and reproducible code and workflows.
Interest in (or foundational understanding of) forest stand dynamics, silviculture, or forest inventory, and interest in (or experience with) integrating remote sensing or geospatial data into ecological or forestry models.

Preferred Qualifications   Experience integrating remote sensing data (e.g., LiDAR or spectral, multi‑platform) into forestry or ecological models.
Familiarity with Canadian forest management contexts, timber supply analysis, yield curve development, or similar applied modelling frameworks.
Experience working with large datasets or database tools (SQL or equivalent).
Equal Opportunity Statement  The University of Alberta welcomes applications from all qualified persons. We encourage women, First Nations, Métis and Inuit persons, members of visible minority groups, persons with disabilities, persons of any sexual orientation or gender identity and expression, and all those who may contribute to the further diversification of ideas and the University to apply.

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