Level

Doctolib

Research Scientist (x/f/m)

Doctolib is hiring a Research Scientist (x/f/m) in Paris, France. Level rates it ; you can apply on Doctolib.

Level's read on this job

  • Level rates this research scientist role Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include PyTorch, Python and Machine Learning Frameworks.
  • Level classifies it as a senior role.
  • Level lists 155 other open roles at Doctolib.

AI in this role

Build and publish clinically reliable AI models of patient health at scale within the Doctolib Clinical AI Research Lab.

pytorchpythonmachine-learning-frameworks
ai-researchmachine-learningresearchhealth-informaticscausal-inferencemultimodal-modeling

Set a new pulse for healthcare!

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 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 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 PhD 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 NeurIPS, 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 PyTorch, 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, 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 the Doctolib Tech site.

What we offer

  • Free comprehensive health insurance (basic package) for you and your children
  • 25 days of paid vacation per year, plus up to 14 days of RTT
  • Free 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 class
  • 50% reimbursement of your public transport subscription
  • ParentCare 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 DoctoGrowth
  • 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 our candidate 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 discrimination.

The 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.

 

How we rate this

Research Scientist (x/f/m) at Doctolib rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI ResearchMachine learningResearchHealth InformaticsCausal InferenceMultimodal ModelingPyTorchPython

Also common in research scientist jobs at this level

Pay

Typical research scientist job
$192k

This posting doesn't list pay. Use the typical research scientist figure when pay comes up. See research scientist jobs

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. Tell me about a project where machine learning was part of your work. What did you do?
  3. Tell me about a project where research was part of your work. What did you do?
  4. Tell me about a project where health informatics was part of your work. What did you do?
  5. Tell me about a project where causal inference was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI Research, Machine learning, Research, Health Informatics, and Causal Inference. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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