Research Scientist

Set a new pulse for healthcareWe are looking for a Research Scientist to join the Doctolab team (Doctolib Clinical AI Research Lab).Your mission is to build accurate, well-calibrated, and clinically reliable models of patient health, learned from health data at scale.

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The work is both fundamental and applied: you publish, and your models reach products used by doctors and patients.

Doctolib is used by around 450,000 health professionals and 90 million people across Europe, and research that succeeds in the lab can be deployed at that scale.Working at Doctolib means contributing to one of Europe's leading health-tech companies, and seeing your work improve care for patients and practitioners.How we workDoctolab is a research lab in its founding phase, so researchers have real influence over its direction and its priorities.

We work closely with the data science and product teams, and we stay close to the data.We expect researchers to explain why a question matters, not only why it is open.

Projects are chosen on both scientific ambition and what they change for patients and practitioners.

The work suits researchers who want to see their results used.The questions we raise are open problems in machine learning: world models that predict the consequences of an action, calibration and uncertainty, causal inference from observational data, multimodal sequence modelling, orchestration between model capabilities.

Results on these questions hold well beyond healthcare.

We are in a strong position to work on them: we have the data to learn a world model from, a clinical use case that defines success, and the engineering path to put it in front of practitioners and patients and learn from what comes back.Experience with healthcare or medical data is a plus but not required.

Both early-career and experienced researchers are welcome.What you'll doYour responsibilities include but are not limited to:Build a world model of patient health: how a health state evolves over time and changes in response to care, learned from observational data with the confounding accounted forBuild evaluation methods that test calibration, robustness, interpretability, privacy, and generalization outside the training distributionWork with the data science and product teams to turn research results into clinical-grade featuresPublish at leading machine learning and health informatics venuesEngage the international health and machine learning community through open collaboration: data challenges, shared benchmarks, and open-source releasesHelp define the lab's research agenda and its working relationship with the rest of the companyWho you areBefore you read on: if you don't have the exact profile described below, but you feel this job description matches your skill set, we still encourage you to apply.You'll be a great fit if you:Have a PhD in machine learning, statistics, computer science, or a related field, or a Master's degree with significant research experienceHave depth in one or more of: representation learning and self-supervised learning; large language models and multimodal modelling; causal inference and causal discovery from observational data; temporal and dynamic modelling; calibration and uncertainty quantification; agentic systems and orchestration; evaluation and benchmarking; privacy auditing of machine learning modelsHave first-author publications at leading venues such as NeurIPS, ICML, ICLR, ACL, EMNLP, or comparable medical informatics venuesHave driven your own research, from choosing the question to publishing the resultAre proficient in Python and a deep learning framework such as PyTorch, and have trained models yourselfAre comfortable working with large and imperfect real-world dataCan explain why a research question matters, scientifically and for patients or practitionersAre fluent in English, the working language of the labIt would be fantastic if you:Have experience with healthcare or medical data, clinical text, or electronic health recordsHave taken research models into production, or worked alongside product teamsHave released open-source code, benchmarks, or datasetsLife at Doctolib TechOur solutions are built on a single fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to country and healthcare specialty requirements.Our stack is composed of Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native.We leverage AI ethically across our products to empower patients and health professionals.

Discover our AI vision here.Want to learn more about our tech culture and environment? Visit theDoctolib Tech site.What we offerFree comprehensive health insurance (basic package) for you and your children25 days of paid vacation per year, plus up to 14 days of RTTFree mental healt