Job offer

The ambition of AGORA is to design and validate one of the first agentic AI platforms fully dedicated to biomedical research and precision oncology. The platform will be capable of exploring complex biological data, integrating the latest medical knowledge, assisting molecular interpretation, and generating novel research hypotheses. To achieve this goal, AGORA combines large language models (LLMs), biomedical knowledge bases, bioinformatics tools, multi-omics datasets, and clinical data into a unified reasoning framework.

The project brings together experts in artificial intelligence, machine learning, and data science, specialists in health data integration and governance, researchers in systems biology and mechanistic modelling, as well as oncologists actively involved in precision medicine programmes.

The successful candidate will work at the interface of these different groups and will join the Bioinformatics Core Facility and INSERM U1331 Computational Oncology Unit, a highly interdisciplinary environment comprising approximately 100 researchers working in computational biology, bioinformatics, and artificial intelligence.

Main Responsabilities

The position is central to the project and aims to develop the scientific and technological foundations of a new generation of AI assistants for oncology.

As a Generative AI and Multi-Agent Systems Engineer (M/F), you will:

• Design and develop multi-agent architectures for biomedical applications.
• Evaluate and benchmark large language models and agentic AI frameworks.
• Develop workflows integrating:
• multi-step reasoning,
• Retrieval-Augmented Generation (RAG),
• bioinformatics and biological modelling tools,
• machine learning and predictive AI models.
• Connect AI agents with biomedical knowledge bases, analysis pipelines, and HPC resources.
• Define evaluation protocols assessing response quality, explainability, robustness, and reliability.
• Collaborate closely with biologists, clinicians, bioinformaticians, and data engineers.
• Contribute to scientific publications and future research projects in AI and precision oncology.

• PhD (or equivalent experience) in Computer Science, Artificial Intelligence, Machine Learning, Bioinformatics, Computational Biology, or a related field.

Technical Skills

• Excellent Python programming skills.
• Strong experience with generative AI and large language models.
• Experience with agentic AI systems or complex orchestration architectures.
• Good knowledge of information retrieval methods, RAG systems, vector databases, and/or knowledge graphs.
• Familiarity with Linux environments and modern software development practices.

Preferred Qualifications

• Experience with LangGraph/LangChain, CrewAI, MCP, or similar frameworks.
• Experience in biology, genomics, digital health, biomedical research, or oncology.
• Scientific publications in AI, machine learning, bioinformatics, or computational biology.

Personal Skills

• Scientific curiosity.
• Innovative mindset.
• Ability to work autonomously.
• Interest in interdisciplinary research.
• Ability to transform exploratory ideas into robust and reusable solutions., PhD or equivalent

Languages ENGLISH

AGORA offers a unique opportunity to help shape the next generation of AI systems for oncology by working on real-world scientific and clinical challenges alongside leading researchers and physicians.

The project brings together several of the most exciting areas of modern artificial intelligence, including large language models (LLMs), multi-agent systems, knowledge graphs, multi-omics data integration, biological modelling, and clinical decision support.

Beyond technology development, the ambition is to explore how agentic AI can become a genuine scientific partner-capable of reasoning over complex biomedical data, integrating up-to-date medical knowledge, supporting molecular interpretation, and generating novel research hypotheses.

At the intersection of fundamental research, data science, systems biology, and precision medicine, Institut Curie provides a world-class research environment with access to unique clinical and molecular datasets. You will work within a highly interdisciplinary team and benefit from significant scientific freedom, opportunities for high-impact publications, international collaborations, and participation in the development of future national and European research initiatives.