PhD Position in Forest Growth Projection and Sampling, University of British Columbia

For many forests of the world, growth models and growth data are vital to plan adaptation strategies under climate change. In reality, both are limited to certain tree species, ecosystem types, and geographical regions. Thus, there is an immediate need to extend the coverage of growth models and data. To do so, we need a projection system that can easily calibrate existing growth models in real-time with incoming growth data from forest ecosystems without a model. Moreover, we also need a cost-effective and efficient inventory system for monitoring forest growth that can be deployed over large areas in such forest ecosystems to complement the projection system. Uncertainties from the projection system and the inventory system must be integrated and propagated through time for assessing risks of an adaptation strategy and better informing management decisions.

We are looking for a highly motivated, enthusiastic, and independent person for a four-year funded PhD position. The overall aims of the position are to develop a projection system based on particle filtering to effectively predict long-term forest growth and an inventory system based on variable probability sampling to efficiently estimate the growth. The specific objectives of the project are: (1) assessing particle filters in projecting growth of a forest ecosystem with models transferred from unrelated regions, (2) evaluating the impact of variable probability sampling methods and estimators on particle filtering, and (3) exploring multiple-model methods of particle filtering in forest growth projection.

Candidates for this PhD position should have:

  • A MSc degree in forest science, forest management, or a related field with strong quantitative skills and training in statistics or a MSc degree in statistics, mathematics, or a related field with a strong interest in forest applications,
  • Knowledge in Bayesian statistics, particle filtering, probability sampling theory, forest inventory, growth and yield modeling, and forest stand dynamics,
  • Experience in R programming,
  • Experience in writing and publishing peer-reviewed articles,
  • Fluency in verbal and written English,
  • Willingness to participate in fieldwork,
  • Ability to work independently and in a team,
  • Ability to contribute to a positive environment in an inclusive and diverse team.

This position will be based at the Department of Forest Resources Management, Faculty of Forestry, the University of British Columbia, Vancouver campus, which is located on the traditional, ancestral, and unceded Musqueam Territory. We strive to create a respectful, positive, and safe working environment for people of all backgrounds. We believe that inclusiveness and diversity are essential to academic excellence. We encourage members of underrepresented groups to apply.

Application deadline is May 01, 2024. The expected pay range for this position is $27,000 - $29,000/year. Start date is flexible but expected to be September 01, 2024. To apply, please prepare:

  • A one-page letter describing your interests and motivation on this research topic and your career goals,
  • A current curriculum vitae,
  • Copies of your academic transcripts,
  • Contact information for three academic references.

Please email all the documents to Tzeng Yih Lam, Assistant Professor in Forest Measurements, Please use “PhD Application: Forest Projection and Sampling” as the email subject. Please also feel free to send inquiries about the position.

We thank all candidates for applying, but only shortlisted candidates will be contacted for interviews.