Senior Staff Research Scientist - Clinical AI Lab (x/f/m)
DoctolibParis, Paris, FrancePosted 30 March 2026
Job Description
What You Will Do
At Doctolib, we're revolutionizing healthcare delivery through advanced AI systems focused on medical reasoning. As a Senior Staff Research Scientist, you'll develop cutting-edge AI solutions that enhance clinical decision-making and support healthcare professionals in their daily practice. You'll work at the intersection of machine learning and healthcare, creating models that can understand medical knowledge, reason through complex clinical scenarios, and assist medical practitioners in providing better care.
Your responsibilities include (but are not limited to):
Solve Real-World Healthcare Challenges : Design and build advanced machine learning models, especially in NLP and large language models, to improve healthcare workflows, enhance patient experiences, and power intelligent health solutions at scale.
Innovate Experiment : Research and prototype novel algorithms and architectures, staying at the forefront of AI/ML developments. Bring new ideas from concept to working prototypes, leveraging the latest advances in deep learning and generative AI.
Collaborate Across Teams : Work closely with product, engineering, medical experts, and other stakeholders to translate business needs into impactful research projects. Communicate technical concepts and results clearly to both technical and non-technical audiences.
Drive Impact : Analyze large, complex data sets to extract actionable insights, define key metrics, and rigorously evaluate model performance.
Share Learn : Advance Doctolib’s AI expertise by sharing findings within the team and with the wider ML community through publications, talks, and workshops. Mentor and support other scientists and engineers in adopting best practices.
Who You Are
Technical Expertise:
PhD or Master’s degree (plus significant experience) in Computer Science, Machine Learning, Mathematics, or a related field; Publications as first author in top-tier AI/ML conferences such as NeurIPS, ICLR, ICML, ACL, EMNLP, or relevant medical informatics venues are a plus;
Deep understanding of machine learning and deep learning concepts, with hands-on experience in NLP, LLMs, or generative AI.
Strong programming skills in Python (and ideally experience with ML frameworks such as PyTorch or JAX).
Familiarity with modern data tools and scalable training on large datasets.
Innovator Problem Solver:
Track record of independently driving research and translating it into real-world applications.
Experience designing experiments, evaluating intrinsic and extrinsic metrics, and iterating quickly.
Curiosity and drive to learn, research, and apply new machine learning techniques.
Collaborative Communicative:
Comfortable working in highly cross-functional teams, with the ability to clearly communicate complex concepts to diverse audiences.
Passionate about sharing knowledge and contributing to a culture of learning and innovation.
Mission-Driven:
Motivated by Doctolib’s mission to make healthcare better for all. Eager to solve meaningful problems with technology.
Detail-oriented, rigorous, and committed to delivering high-quality, production-ready solutions.
What we offer
Free comprehensive health insurance 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
Parent Care Program: receive one additional month of leave on top of the legal parental leave
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 inte ... (truncated, view full listing at source)
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