Jul 1, 2022

Postdoctoral Scholar: Embodied Carbon Benchmarks-WBLCA

Research Position Now Open

Postdoctoral Scholar: Benchmarks for North American Buildings using whole-building life cycle assessment (WBLCA)

The Department of Architecture at the University of Washington in Seattle is seeking a post-doctoral research scholar to conduct advanced research on the environmental impact of buildings and building materials. The position is part of an Alfred P. Sloan Foundation funded research project led by the Carbon Leadership Forum. The project will develop a database of whole building life cycle assessment (WBLCA) models in collaboration with architecture and engineering firms across North America. The database will be used to generate North American building baselines figures along with analysis of model variability and uncertainty. The position is based in Seattle WA, has a duration of 2 years with a possible extension to 4 years. The post-doctoral scholar will be working under the supervision of Kate Simonen.

The review process is competitive and based on academic record. Applicants should submit cover letter, full CV and any other materials detailing academic and professional experience as well as research interests to clfinfo@uw.edu. Candidates interested in this position are encouraged to contact Prof. Kate Simonen or Stephanie Carlisle with any questions. Review of applications will start on 07/01/2022 but will remain open until the position is filled.

Postdoctoral scholars are represented by UAW 4121 and are subject to the collective bargaining agreement, unless agreed exclusion criteria apply.  For more information, please visit the University of Washington Labor Relations website.

Requirements:

  • Candidates are required to have a PhD in Architecture, Engineering, Environmental Science, or a related field. Foreign equivalents will be accepted.
  • Highly-motivated and independent researcher with a demonstrated record of scholarship in Life Cycle Assessment and Building Technology, including but not limited to material science and engineering, data science and statistical analysis.
  • Strong life cycle assessment modeling skills, interest in open-source development, data management, and the Python programing language.
  • Good communication and writing skills.

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