Postdoctoral Fellow in Environmental Studies: Clean Energy Policy and Generative AI at Dartmouth College
Postdoctoral Fellow in Environmental Studies: Clean Energy Policy and Generative AI at
Dartmouth College
.
This is a
postdoctoral
opening at the intersection of
Environmental Science
,
Clean Energy Policy
,
Energy Governance
,
Computational Social Science
,
Computer Science
, and
Natural Language Processing
. The fellow will work on expert-in-the-loop workflows that combine generative AI, domain expertise, and qualitative methods to address information overload and institutional risks in energy policy and governance.
The project focuses on creating and evaluating LLM-based approaches to scale qualitative analysis of policy, regulatory, legal, and stakeholder documents in reproducible ways, with applications to offshore wind, transmission, and battery storage. The fellow will be advised by
Professor Elizabeth J. Wilson
and will work closely with
Simon Stone
from Dartmouth Research Computing and partners at
DTU Wind
in Denmark.
Eligibility highlights include a Ph.D. in a relevant field (or ABD with degree by the start date), demonstrated experience with LLMs/GenAI, Python or R, computer clusters, and Linux servers, plus strong analytical and communication skills. Preferred experience includes energy policy/governance, qualitative methods, NLP, multimodal embeddings, similarity search, retrieval pipelines, hierarchical/statistical models, and evidence of research success.
The position is full-time, in residence in Hanover, New Hampshire, and non-remote. The initial appointment is for one year, with possible renewal depending on funding and performance. Salary and benefits are competitive and aligned with Dartmouth postdoctoral guidelines.
Applications are submitted via Interfolio and should include a cover letter, CV with three references, a one-page research statement, and two representative publications or writing samples.
