For more information, please follow this link: http://placeslab.org/postdoc

Salary– DOE

The PLACES lab at Boston University (BU) is offering an NSF-funded position for a postdoctoral
researcher or research scientist with a strong skillset in spatiotemporal statistics, machine
learning, or causal inference, and an interest in land conservation policy in the United States.
The successful candidate will contribute to the development of U.S.-wide, parcel-level
estimates of land value and the cost of long-term conservation (land purchase, easements)*.
Products will support policy analyses and decision-making processes of academic, federal, and
non-profit stakeholders interested in identifying effective and equitable land use choices under
the federal administration’s current initiative to protect 30% of the U.S. by 2030. The research
will be funded under NSF’s Human-Environment & Geographical Sciences program.
The researcher will have the last opportunity to work with a unique and fascinating dataset that
is scheduled to expire on Sept 30, 2023: geospatial data of 150 million U.S. properties and sales
with a wide range of social and environmental characteristics (placeslab.org/dictionary).
Research priorities will be defined jointly. Creative extensions are welcome.
The ideal candidate will have:
• A PhD (or similar experience) in economics, statistics, data science, geography,
environmental science, or a similar field with a strong quantitative research profile.
• Prior experience with geospatial statistics, machine learning, and/or econometrics
(in particular causal inference from observational data).
• An emerging publication record in peer-reviewed journals.
• Interest in understanding land conservation policy in the United States.
Knowledge in the following domains will be an asset (but not expected):
• Geospatial packages in Python (geopandas, rasterio, etc.)
• Parallelized computing (Linux, SunGrid).
• Principles of land and easement valuation.