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Raidium is seeking an enthusiastic intern to build a scalable support function for its AI-native radiology platform. You will map processes, design a compliant QMS, and develop automations that create and route tickets, with alerts for late responses. The role includes KPI tracking and delivering a production-ready dashboard.
Join the Clinical Solutions team to deploy in hospitals, work with radiologists and IT teams, and contribute to process improvements in a regulated SaMD environment.
As Raidium deploys its AI-native viewer in more hospitals across Europe and the US, every radiologist and hospital IT team we work with needs fast, reliable answers. Your mission is to build the support function that makes this possible at scale: a structured, compliant process, smart automations and clear KPIs, so that every request is tracked and answered on time.
You will join the Clinical Solutions team, the customer-facing team that deploys Raidium in hospitals and works with radiologists and hospital IT teams day to day. Building the support function is your main focus and internship deliverable, but you will be a full member of the team: taking part in its daily life, giving a hand on deployments and partner requests when needed, and helping improve our processes in general.
You will be managed by Nicolas Pageaud, within the Clinical Solutions team led by Claude Magnard.
We are looking for someone who:
Raidium is building the first AI-native radiology viewer, with 3D multimodal foundation models built in for precision radiology. The first use cases focus on oncology and clinical trial biomarkers, and the viewer is expanding to the whole radiology workflow. Raidium raised a €16M seed round in November 2024 and is growing its team ahead of a Series A.
Raidium's founders came from Owkin and are experts in radiology and machine learning.
Pierre Manceron, CEO, is a Centrale Paris + MVA engineer specialized in Applied Mathematics and Machine Learning. He previously led machine learning projects at Owkin.
Paul Herent, Chief Medical Officer, is a radiologist and former interne des hôpitaux de Paris, with a Cogmaster (ENS) and PSL background. He has published pioneering research on deep learning in radiology.
Our team brings together medical, AI and business expertise from top-tier schools and companies (Polytechnique, CentraleSupélec, Ponts, MVA, Owkin, Cardiologs, Datadog) to transform radiology through cutting-edge technology.