Research Scientist - Privacy-Preserving and/or Distributed Learning

Owkin is hiring!


Efficient Data. Effective Medicine

OWKIN uses AI and machine learning to augment medical and biology research. Its proprietary platform, Owkin Socrates, uses machine learning technology to integrate biomedical images, genomics and clinical data to discover biomarkers and mechanisms associated with diseases and treatment outcomes. The company develops scientific collaborations with top-tier medical institutions and partners with leading pharmaceutical companies. Owkin has developed a state-of-the-art federated learning technology in healthcare to overcome the sharing problems associated with medical data, building collective intelligence from distributed data at scale while preserving privacy and security.

Our data scientists are among the best in the world, with several Kaggle Masters, DREAM Challenge top performers, and publications in ICML, NIPS and other top scientific journals. OWKIN is proud of its unique physician-scientist team trained in Weill Cornell and Paris University as well as pharma and CRO senior directors from Novartis, Roche, and Parexel.. Owkin is backed by renowned investors — such as Google Ventures and F-Prime — as well as a distinguished scientific board chaired by Bruno Strigini, former CEO of Novartis Oncology. To build this vision, Owkin is growing rapidly, with offices located in the USA, France, and UK.

Job Description


Federated learning is the process through which a predictive model is simultaneously learned across multiple sites, while ensuring that no data, and only very little information overall, leaves each site. At Owkin, we seek to better understand and to improve this process. Our research encompasses many different subjects, ranging from communication-efficient distributed algorithms to privacy-preserving techniques such as differential privacy and secure multi-party computation.

Owkin is a company with a strong academic culture. In our lab, we aim not only to improve our products, but also to develop fundamental research that is aligned with the company's objectives. As such, this is a great opportunity for those looking to combine the freedom of academia to the benefits of working in industry.

The position is located in OWKIN Lab, our Paris-based R&D center. Candidates not meeting every criteria, but who can demonstrate exceptional skill in key areas, are invited to apply.

Preferred Experience


  • PhD or equivalent degree in Computer Science, Electrical Engineering, Physics, Mathematics, Statistics or any other related field
  • Passionate about doing research and writing papers
  • Publications in one of the following subjects, or other related ones: communication-efficient distributed protocols, distributed learning algorithms, transfer learning, privacy-preserving machine learning, differential privacy, secure multi-party computation
  • Expertise coding in Python, strong grasp of programming best-practices (e.g. code clarity, documentation, git, etc.)


  • 1+ years of experience developing research as a post-doc
  • Has already developed code within a team or open-source project
  • Knowledgeable in machine learning/deep learning concepts and implementation, or interested to learn more
  • Publications in high-impact journals and conferences


  • ... enjoy working in a small, passionate team where your contributions will have a direct impact
  • ... value process, standards, communication, and code quality
  • ... want to help build never-before-seen technologies


  • Competitive remuneration
  • International and high-profile team
  • Regular social events

Recruitment Process

When submitting your CV, please include the following documents along with your personal CV:

  • A one-page cover letter detailing the relationship and possible interactions between your work and federated & privacy-aware machine learning
  • Your full list of publications
  • Two academic references (may be contacted after first interview)

Additional Information

  • Contract Type: Full-Time
  • Location: Paris, France (75010)
  • Education Level: PhD and more
  • Experience: > 2 years