Stockholm Environment Institute (SEI) is looking for an early-career Research Associate to apply and develop AI and automation approaches across the evidence synthesis process, from literature searching and eligibility screening to (meta)data extraction. The role is a full-time, fixed 12-month contract with possibility of extension subject to funding, based at SEI HQ in Stockholm, Sweden, within the International Climate Risk and Adaptation Team.
The role combines hands-on evidence synthesis with the development and evaluation of AI-driven approaches to make evidence synthesis more efficient, contributing to new meta-research on how automated and AI-based tools can speed up and improve evidence synthesis in the environmental field without compromising reliability, robustness or scientific quality.
Key responsibilities:
- Conduct and support manual literature searching, screening and (meta)data extraction for evidence synthesis projects, working with large volumes of scientific publications and grey literature.
- Develop and maintain reproducible workflows in Python and/or R for screening, extraction, classification, quality-checking, cleaning and harmonization of textual and bibliographic data.
- Apply and evaluate machine learning, natural language processing and LLM-based methods for text classification, information extraction and document analysis.
- Validate automated and AI-generated outputs against human decisions, quantifying errors, uncertainty and potential biases.
- Document methods, decisions and validation procedures to support transparent and reproducible research.
- Work collaboratively with researchers across environmental, sustainability, climate, energy and social science.
Requirements:
- A master's degree in data science, computer science, engineering, socio-environmental science, sustainability science or a related field.
- Early-career experience (1-2 years) in academic or applied research involving data analysis and AI/data-driven methods.
- Programming and data analysis skills in Python and/or R, including version control with GitHub.
- Experience handling large volumes of structured and unstructured text, and practical experience applying machine learning, NLP or large language models to text classification, information extraction or eligibility screening.
- Interest in evidence synthesis methodology and knowledge of, or interest in, sustainability or environmental research.
- Collaborative, analytical, systematic, a clear communicator, and curious and adaptable.
Desirable: experience with literature reviews (systematic, scoping, rapid), bibliographic datasets, and literature eligibility screening or (meta)data extraction.
Offer: collective agreement including occupational pension, annual healthcare contribution, professional development opportunities, flexible working hours with a 37.5-hour workweek and generous vacation. Once employed, you must live in Sweden, preferably in the Stockholm area; remote work from another country is not possible.
Deadline: 26 October 2026
HOW TO APPLY:
Submit your application through the SEI recruitment system (Apply now button) in English, no later than 26 October 2026, 23:59 Stockholm local time. Include a cover letter highlighting relevant qualifications and experience (max two pages) and a curriculum vitae (max four pages). Incomplete applications will not be accepted. Inquiries about the position can be directed to Biljana Macura, Senior Research Fellow, SEI.
https://web103.reachmee.com/ext/I012/1211/job?site=6&lang=UK&validator=4687e906bb0fd747e99188e22d01bed9&job_id=454