PhD student: Applying Machine Learning to Building Systems

4 weeks ago

Vancouver, Canada International Society for Industrial Ecology Full time
PhD student: Applying Machine Learning to Building Systems

There have been growing efforts and advocations for integrating energy performance and carbon intensity metrics into building codes. One of the major technical barriers is the lack of a standard building archetype database and a consistent comparison method for the practitioners and the regulating body. This PhD project aims to remove this technical barrier.

Responsibilities include:

  • Create a bill-of-material (BoM) database for common building archetypes in Canada. A consistent BoM database is critical for understanding the opportunity to reduce carbon intensity in built environment. In addition, the database should include generic building archetypes (i.e., a collective description of building functionality, geometry, operational parameters and thermal characteristics) that are representative of existing and future (e.g., “net-zero energy”) building stocks in Canada. Create a data collection template and a streamlined data extraction tool (programmed in python) for the collection and curation of the BoM database.
  • Develop a set of attributes (e.g., based on climate factors and occupants’ activities) to define the functionality of building archetypes. Develop machine learning models to identify functionally-equivalent archetypes (i.e., having the same set of attribute values).
  • This PhD position is for four years, with a stipend of $CAD 30,000 per annum.
  • The anticipated start date is January 2025.
Required qualifications of the applicant:
  • Completed a Master’s degree in Civil Engineering or other relevant disciplines.
  • Be highly motivated, organized, and a good communicator (written and verbal).
  • Enjoy working in a team environment.
  • Working knowledge of whole-building life cycle assessment.
  • Proven python programming experience: e.g., github repo, scripts, publications.
  • Proven experience in machine learning: e.g., github repo, scripts, publications.
  • Language test score.
  • The minimum TOEFL internet-based score required for a Forestry graduate program application is 100, with a minimum score in each component: Reading – 23; Writing – 24; Listening – 23; Speaking – 22.
  • For IELTS, a minimum overall band score of 7.0 is required, with a minimum score of 6.5 in each component of the academic (NOT general) test.
Additional qualifications of the applicant (i.e., good to have):
  • Proven experience with life cycle assessment: e.g., peer-reviewed publications, technical reports.
How to apply

All qualified candidates are encouraged to apply. The SBR group has and will continue to nourish a safe, supportive and inclusive environment for all its members. We particularly encourage applications from members of groups that have been marginalized on any grounds enumerated under the BC Human Rights Code, including sex, sexual orientation, gender identity or expression, racialization, disability, political belief, religion, marital or family status, age, and/or status as a First Nation, Metis, Inuit, or Indigenous person.

Please apply by emailing Dr. Qingshi Tu (Qingshi.tu@ubc.ca) with the following document as a single PDF attachment:

#J-18808-Ljbffr

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