AI-Powered Evidence Synthesis Researcher

Stift-the-Stockholm-Environment-Institute,-Se; Stockholms kommun; On-site; SEK 420,000 - 560,000; Full time

Benefits offered by this job

Collective Agreement incl.occupational

Occupational pension

Annual healthcare contribution

Health check-ups

Flexible working hours

37.5-hour workweek

Generous vacation days

Job summary

Stift The Stockholm Environment Institute, Sei is seeking an early-career researcher to combine hands-on evidence synthesis with AI-driven workflows. You will perform manual literature searching and data extraction while building reproducible Python/R pipelines for automation and validation.

You will collaborate across environmental and sustainability research teams, applying ML, NLP and LLM methods to improve evidence synthesis without compromising rigor, transparency or scientific quality.

Qualifications

• Programming and data analysis skills in Python and/or R, including version control with GitHub.
• Experience handling large volumes of structured and unstructured text.
• Practical experience applying machine learning, NLP or large language models to text classification, information extraction or eligibility screening.
• An interest in evidence synthesis methodology.
• Knowledge of, or interest in, sustainability or environmental research.
• Experience with more advanced AI development, such as model fine-tuning or deployment, is welcome but deep expertise in machine learning or software engineering is not required.
• Early-career experience (1–2 years) in academic or applied research involving data analysis and AI/data-driven methods.

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 (including bibliographic information and textual data).
• 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.

Skills

Python

R

Machine Learning

NLP

Education

Master’s degree in data science, computer science, engineering, socio-environmental science, sustainability science or a related field.

Tools

GitHub

Job description

Stift The Stockholm Environment Institute, Sei is seeking an early-career researcher to combine hands-on evidence synthesis with AI-driven workflows. You will perform manual literature searching and data extraction while building reproducible Python/R pipelines for automation and validation.

You will collaborate across environmental and sustainability research teams, applying ML, NLP and LLM methods to improve evidence synthesis without compromising rigor, transparency or scientific quality.