Postdoc position: Boston University: large-scale property analytics for conservation planning and natural hazard risk assessment
Christoph Nolte
Dear colleagues,
The PLACES lab 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 and an open-source framework for scalable property analyses built on a decade of related efforts.
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 (NSF CoPe)
- High-resolution prediction and uncertainty estimation of land value and conservation costs (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 (chrn...@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.