[ES_JOBS_NET] Fwd: Postdoc position: Boston University: large-scale property analytics for conservation planning and natural hazard risk assessment

[Christoph Nolte]

Dear colleagues,


The PLACES lab <http://placeslab.org> at Boston University (BU) is seeking
a postdoctoral research scholar to lead and publish large-scale,
property-level analyses of land value, building value, and hurricane damage
risk across the United States, supported by NSF funding.



The position contributes to the development of public datasets and novel
algorithms for U.S.-wide, property-level estimates of land value, building
value, and economic risk from hurricane damage. It supports efforts to
publish a nationwide parcel-level land value dataset
<https://places-conus.readthedocs.io> and an open-source framework for
scalable property analyses <https://github.com/chrnolte/openplaces> built
on a decade of related efforts <https://placeslab.org/places/>.



The successful candidate will have leeway in shaping the direction of the
research to build a strong, competitive researcher profile. Options for
emphasis include: methodological (econometrics, machine learning, computer
vision) and applications (hazards, conservation), with publication venues
in applied economics, geography, conservation planning, and remote sensing.
The position is ideal for early career researchers interested in building a
profile around scalable property-level analyses, including fair valuation,
damage modeling, and/or hedonic valuation.



The ideal candidate will have:

   - A PhD (or similar experience) in economics, statistics, data science,
   geography, environmental science, computer science, or a related field of
   applied statistics.
   - Strong quantitative skills in one or more of the following: scalable
   spatio-temporal statistics / econometrics, machine learning, computer
   vision for extracting building attributes from aerial or street-level
   imagery.
   - An early publication record in peer-reviewed journals.
   - Enthusiasm about contributing to open science frameworks (FAIR data,
   open code).
   - A strong interest in applied environmental policy questions in the
   United States.

Knowledge in the following domains will be an asset (can be taught if
needed):

   - Geospatial processing in Python (e.g., geopandas, rasterio/xarray)
   - High-performance computing (e.g., Sun Grid Engine or similar cluster
   environments)
   - Principles of property valuation and/or hurricane risk estimation
   - Git-based collaborative development with clean APIs and documentation

Expected outputs:

   - Peer-reviewed journal articles (lead-authored encouraged)
   - Public data releases
   - Open-source software modules
   -  Policy-relevant outputs (optional)

This is an 18-month position, supported by two ongoing NSF projects:

   - Coastal hazards, economic prosperity, and resilience
   <https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2209190&HistoricalAwards=false>
   (NSF CoPe)
   - High-resolution prediction and uncertainty estimation of land value
   and conservation costs
   <https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2149243> (NSF HEGS)

The position comes with a strong expectation of renewal, contingent on the
success of grants to which the candidate will have the opportunity to
contribute.



The position starts as soon as possible. In-person availability is
preferred. Fully remote work is an option for exceptional candidates with
demonstrated productivity. BU offers a competitive salary ($75K) and
benefits package.



Interested applicants should contact Associate Professor Christoph Nolte (
chrnolte at bu.edu) with their CV, a letter of interest that includes a
statement of fit with the position (1-2 pages), publications, and contact
information of 2-3 letter writers. Please include the words “NSF postdoc”
in your message header.



Review of applications will begin on Jan 26, 2026, and occur on a rolling
basis until the position is filled. For updates on the status of this
search, visit: placeslab.org/postdoc.



BU is an equal opportunity employer and all qualified applicants will
receive consideration for employment without regard to race, color,
religion, sex, national origin, disability status, protected veteran
status, or any other characteristic protected by law.
-- 
*Christoph Nolte* he/him
Associate Professor
Earth & Environment
Boston University
chrnolte at bu.edu
placeslab.org
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