Senior Staff Research Scientist - Clinical AI Lab (x/f/m)

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, o