The SPIRES Lab at Yale School of the Environment invites applications for a Postdoctoral Associate to join a funded project on digital monitoring, reporting and verification for natural climate solutions and conduct other work in the area of remote sensing-enabled social science.
General work
The postdoctoral associate will conduct the following tasks to contribute to various projects:
- Satellite data access and preprocessing
- Supervision of ground-truth labeling activities
- Machine learning for spatiotemporal data
- Embeddings from visual transformers
- Causal analysis
The Postdoctoral Associate will also contribute to projects related to digital Monitoring, Reporting, and Verification (dMRV) for Natural Climate Solutions (NCS) carbon crediting (X% of time). The dMRV project is a part of SHIFT CM, a TNC-Yale initiative aiming to advance the science behind NCS credit markets. This project will contribute to the science behind dMRV for NCS markets by:
- Synthesizing available scientific evidence on dMRV approaches
- Collating field-collected and remote sensing datasets for NCS projects
- Testing and validating dMRV protocols
Responsibilities
- Lead development and application of a research pipeline for socio-environmental research questions
- Advance the use of visual transformer embeddings for social science applications
- Collaborate on active learning, debiasing, and statistical method development
- Contribute to R package development and dissemination
- Contribute to an evidence-based “good practice guidance” paper for implementing dMRV in
NCS credit markets. - Lead data management and collation of ground-truth project datasets to test dMRV protocols against.
- Contribute to a dMRV accuracy assessment, including a dMRV accuracy assessment “good practice guidance” white paper and an empirical publication testing and validating dMRV approaches.
- Mentor undergraduate research assistants and engage with the research community
Qualifications Required:
- Ph.D. in environmental science, political science, economics, geography, statistics, computer science, or related field
- Experience with remote sensing data analysis
- Strong skills in R programming and/or machine learning for spatial data
- Track record of scholarly publications
Preferred:
- Experience applying remote sensing in social science or policy evaluation
- Familiarity with causal inference methods
- Experience with visual transformers, embeddings, or other modern ML architectures
- Experience with open-source software development and collaborative coding
- Familiarity with carbon markets
- Experience with Google Earth Engine
Position Details
- Appointment: 1 year, with potential renewal for a second year
- Salary: $68,500/year plus benefits
- Start date: Early 2026
- Location: New Haven, Connecticut
Application Instructions
To apply, please send the following to luke.sanford@yale.edu:
- Cover letter describing your fit for the position
- CV
- Two representative publications or preprints
- Contact information for three references