Research Scientist (x/f/m)

We 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. 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 work

Doctolab 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 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 do

Your 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 for

Build evaluation methods that test calibration, robustness, interpretability, privacy, and generalization outside the training distribution

Work with the data science and product teams to turn research results into clinical-grade features

Publish at leading machine learning and health informatics venues

Engage the international health and machine learning community through open collaboration: data challenges, shared benchmarks, and open-source releases

Help define the lab's research agenda and its working relationship with the rest of the company

Who you are

Before 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 Ph

D in machine learning, statistics, computer science, or a related field, or a Master's degree with significant research experience

Have 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 models

Have first-author publications at leading venues such as Neur

IPS, ICML, ICLR, ACL, EMNLP, or comparable medical informatics venues

Have driven your own research, from choosing the question to publishing the result

Are proficient in Python and a deep learning framework such as Py

Torch, and have trained models yourself

Are comfortable working with large and imperfect real-world data

Can explain why a research question matters, scientifically and for patients or practitioners

Are fluent in English, the working language of the lab

It would be fantastic if you:Have experience with healthcare or medical data, clinical text, or electronic health records

Have taken research models into production, or worked alongside product teams

Have released open-source code, benchmarks, or datasets

Life at Doctolib Tech

Our 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, Type

Script, Java, Python, Kotlin, Swift, and React 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 the

Doctolib Tech site.

What we offer

Free comprehensive health insurance (basic package) for you and your children25 days of paid vacation per year, plus up to 14 days of RTTFree mental health and coaching services through our partner Moka.care

Work from abroad for up to 10 days per year thanks to our flexibility days policy

Lunch vouchers (Swile card) worth 8.50 per working day, with 4.50 covered by Doctolib

A subsidy from the work council to refund part of the membership to a sport club or a creative class50% reimbursement of your public transport subscription

Parent

Care Program: Enjoy full salary coverage (100%) during your first month of birth leave and 75% during the second, covered by Doctolib

Enrollment in Doctolib's long-term employee value sharing plan called Docto

Growth

For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support

Relocation support in case of international mobility

Access to the best AI tools for coding, development and dedicated training

Our interview process

Recruiter Interview

One or more Research Background Interviews

Technical / Problem-Solving Interview

Behavioral Interview

At least one reference check

We want your experience to be clear, respectful, and transparent. Learn more about our hiring process on ourcandidate experience page.

Job details

Permanent position

Full-time

Paris, France

Hybrid work setup (up to 2 remote days per week)

Start date: as soon as possible

We welcome everyone

At Doctolib, we are committed to improving access to healthcare for everyone. This translates into our recruitment process. We evaluate candidates based solely on qualifications and motivation, without any form of more diverse ideas are heard, the more our product will truly improve healthcare for all. You are welcome to apply to Doctolib, regardless of your gender, religion, age, sexual orientation, ethnicity, or disability.

To ensure equal opportunities, we invite you to exclude personal information (e.g., pictures, age) from your applications. If you require any accommodation, please let us know for support during the hiring process.

Join us in building the healthcare we all dream of!

Your data privacy

All information provided is processed by Doctolib for application management. For data processing details, click

France. Please contact hr.dataprivacy(at)doctolib.com for inquiries or to exercise your rights.