Research associate: AI
Core
Develop and evaluate AI-driven workflows to automate evidence synthesis processes for environmental research, combining manual literature screening with machine learning and NLP methods.
Role type
Research associate (AI & Evidence Synthesis)
Builds
Automated screening, classification, and extraction workflows for scientific publications and grey literature
Domain
Environmental science, sustainability, climate risk, and evidence synthesis
Deliverable
production ML models
Required skills
Python, R, machine learning, natural language processing, LLMs, version control (GitHub), data analysis, literature searching, systematic reviews
Preferred skills
Model fine-tuning, deployment, bibliographic dataset management, sustainability research background
Technologies
Python, R, GitHub, LLMs
Responsibilities
Conduct manual literature searching, screening, and data extraction; Develop reproducible workflows for data cleaning and harmonization; Apply and evaluate ML/NLP/LLM methods for text classification and extraction; Validate automated outputs against human decisions; Document methods and validation procedures; Collaborate with researchers across environmental and social sciences
Seniority
Early-career, 1–2 years experience
