ARIA - Literature Review AI Automation (IT-PW-WDA-2026-165-GRAP)

ARIA/CAiMIRA is a joint WHO-CERN project that models the airborne transmission of respiratory pathogens and develops an automated, structured, and transparent systematic literature review process to inform public health policy and guidance. It builds on CERN's expertise in data management and knowledge systematisation. The planned second phase will extend the project to other airborne pathogens and to indoor air quality.
Work Package 4, "NLP Mechanisms for Systematic Literature Reviews," will continue automating the systematic review process and associated data analysis using AI-based methods. Within this work package, the QUEST graduate will spend 12 months bringing the NeutrinoReview prototype to production.
Your responsibilities:
Design the architecture and concept for the production version of NeutrinoReview.
Establish a detailed development roadmap with clear milestones.
Develop guidelines for the safe and responsible integration of AI into systematic review workflows.
Release NeutrinoReview as a production-ready, general-purpose tool for domains beyond public health, including IT and physics.
Your profile:
Extensive experience in ML/NLP-based data science.
Strong expertise in systematic literature review workflows and methodologies.
Recognised expertise in AI-assisted research tools.
Proficiency in full-stack development and DevOps practices.
Hands-on experience deploying applications on Kubernetes/OpenShift.
Skills:
Programming: Advanced proficiency in Python, JavaScript and React.
UI/UX: Design and development of intuitive, user-centred interfaces.
Systematic reviews: Strong expertise in systematic literature review workflows and methodologies.
AI/NLP: In-depth experience designing and deploying AI and NLP pipelines.
DevOps: Solid working knowledge of DevOps practices, including CI/CD and containerisation.
Spoken and written English, with a commitment to learn French.
Eligibility criteria:
You are a national of a CERN Member or Associate Member State.
You have a professional background in Data Science (or a related field) and have either:
a Master's degree with 2 to 6 years of post-graduation professional experience;
or a PhD with no more than 3 years of post-graduation professional experience.
You have never had a CERN fellow or graduate contract before.

Employment type
Full-time

Work arrangement
Hybrid