** May 2022: I am not currently recruiting new students. I will post future openings here. If you wish to inquire about possible positions (e.g., funded by a fellowship/scholarship), please email me with the materials described below. Note that I’ll only respond to emails that are a good match for my interests and schedule **

At the University of British Columbia, I am looking for enthusiastic, disciplined, and collegial graduate students in Ph.D. in Forestry or Master of Science in Forestry. A full funding package (4 years for Ph.D. and 2 years for Master’s) will include stipends, a personal computer, travel support (to present at conferences), and physical lab space.

If interested, please email me at keun.park@ubc.ca with the following:

  • A brief statement (1-2 paragraphs) of your research interests and reasons for wanting to join my research group
  • Your CV
  • Your academic transcripts (unofficial)
  • Writing samples that you are most proud of (e.g., publication, thesis)
  • Whether or not you have applied for external funding or intend to (see examples here)
  • Your favourite city and the reason 🙂

My mentoring philosophy is to ensure that all students, irrespective of their backgrounds, are provided multiple opportunities to make a contribution to advance science in urban forestry and related fields while being engaged and connected to real world issues. I try to foster a welcoming learning environment that encourages a growth mindset, respect for diversity, analytical thinking, and peer-to-peer training.

I recognize that historically, racial, ethnic, and gender diversity is lacking is urban forestry compared with other disciplines (Bardekjian et al., 2019; Kuhns et al., 2002, 2004; Urban Forestry, 2020). One of my core training goals is to involve students of various backgrounds because I believe that diversity can generate more ideas. Creativity led by diversity can innovate the integration of digital technology with urban forestry design and planning, which is related to my key research areas. To promote an equitable, diverse, and inclusive learning environment, I recruit and mentor underrepresented students, allow flexible time management (e.g., accommodating family care time), enhance cross-cultural collaboration beyond my research group, and pursue research that benefits underrepresented communities (e.g., environmental justice, green equity, systemic bias in demographics).

Other helpful links

Previous posts

  • Project title: Developing automated visitor monitoring tools for better management of urban nature
  • Project program and period: NSERC Discovery Grant (2022-2027)
  • Overall research question: How can we monitor and predict the usage dynamics in urban parks and greenways in a reliable and efficient way?
  • Research objectives
    1. Develop reliable and valid visitor monitoring tools in parks and greenways using sensors
    2. Automate the behaviour mapping process in parks and greenways through the combination of sensors and drones
    3. Estimate visitor volume and movements using spatiotemporal models
  • Skills/interests needed: digital technology (sensors, drones, etc.), programming language (python, R, SQL, etc.), machine learning algorithms, observational research

Key topics, skills, and research interests include (please note that you can work on related topics that you have developed):

  1. Role of urban forestry design and planning in urban developments
    • Overall research question: What are the role and impacts of urban forestry design and planning in sustainable urban developments?
    • Skills/interests needed: design/planning education background (e.g., landscape architecture, urban planning and design), GIS and/or statistics, mixed-methods research (case studies, quasi-experiments, statistical analysis)
  2. Effective monitoring of urban parks and forests usage
    • Overall research question: How can we monitor and predict the usage dynamics in urban parks and greenways in a reliable and efficient way?
    • Skills/interests needed: digital technology (sensors, drones, etc.), computer programming (python, R, SQL, etc.), machine learning algorithms, observational research
  3. Access to urban parks and forests of varying sizes and forms
    • Overall research question: How do we connect low-mobility population (e.g., children, older adults, people with disabilities, low income people) with different sizes and types of urban parks and forests?
    • Skills/interests needed: GIS, statistics, multidisciplinary interests (forest management, environmental justice, urban design and planning, transportation, etc.)