PhD in Sampling Theory for Forest Growth

For many forest ecosystems, growth models and growth data are vital to plan adaptation strategies under climate change. To support development of growth models under uncertain future climates, forest monitoring systems are important to gather the necessary information. The systems ideally consist of measurement methods and sampling strategies that are adaptive, efficient, and targeted to individual growth components. Moreover, the monitoring systems must be cost-effective so that they can be deployed over large areas. This feature is particularly important for forest ecosystems that are lacking growth models and long-term monitoring programs. Lastly, uncertainties from the inventory systems must be integrated into growth models to assess risks of adaptation strategies and management decisions.

We are looking for a highly motivated, enthusiastic, and independent person for a four-year funded PhD. The overall aims are to develop efficient forest monitoring systems for assessing forest growth. The specific objectives of the project are to: (1) design innovative technologies to measure tree growth, (2) develop cost-effective and efficient sampling strategies to assess forest growth components, and (3) assess and integrate sources of uncertainty.

Candidates for this PhD 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 statistics, probability sampling, forest inventory, forest management, 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.

The PhD 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 01 December 2024. The expected funding for this position is $27,000 - $30,000/year. Start date is flexible but expected to be 01 September 2025. To apply, please prepare:

  • A one-page letter of intent 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, tzengyih.lam@ubc.ca. Please use “PhD Application: Sampling Theory for Forest Growth” as the email subject. Please also feel free to send inquiries about the PhD.

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

 
Reference Number

Please mention reference number GPS-58214 in all your correspondence about this Doctoral student position.

This position will be supervised by
Interested applicants will have to gain admission to this graduate program
 
 
 
 
 

Follow these steps to apply to UBC Graduate School!