ARIA Literature Review AI Automation Graduate (Data Science)

About the role

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. Work Package 4, "NLP Mechanisms for Systematic Literature Reviews", continues to automate the review process and data analysis with AI-based methods. The QUEST graduate will spend 12 months bringing the NeutrinoReview prototype to production.

Key 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.

Required profile

• National of a CERN Member or Associate Member State.
• Professional background in Data Science (or a related field).
• Either a Master's degree with 2 to 6 years of post-graduation experience, or a PhD with no more than 3 years of post-graduation experience.
• No previous CERN fellow or graduate contract.
• Spoken and written English, with a commitment to learn French.

Required skills

• Advanced Python, JavaScript and React.
• Full-stack development and DevOps, including CI/CD and containerisation.
• Hands-on deployment on Kubernetes/OpenShift.
• AI/NLP pipeline design and deployment.
• Systematic literature review workflows and methodologies.

What we offer

• Monthly net stipend of 6,372 or 7,004 Swiss Francs depending on degree.
• 30 days of paid leave plus 2 weeks annual closure.
• CERN health insurance coverage and pension fund membership.
• Family, child and infant allowances and a relocation package.
• Contract of 12 months, extendable up to 36 months, with hybrid work and a target start of 1 December 2026.
• On-the-job and formal training including language classes.