PhD Position F/M PhD student on privacy-preserving federate learning with applications in oncology

Le descriptif de l’offre ci-dessous est en Anglais

Type de contrat : CDD

Niveau de diplôme exigé : Bac + 5 ou équivalent

Fonction : Doctorant

Niveau d'expérience souhaité : Jusqu'à 3 ans

A propos du centre ou de la direction fonctionnelle

The  Inria University of Lille centre, created in 2008, employs 360 people  including 305 scientists in 15 research teams. Recognised for its strong  involvement in the socio-economic development of the Hauts-De-France  region, the Inria University of Lille centre pursues a close  relationship with large companies and SMEs. By promoting synergies  between researchers and industrialists, Inria participates in the  transfer of skills and expertise in digital technologies and provides  access to the best European and international research for the benefit  of innovation and companies, particularly in the region.For more  than 10 years, the Inria University of Lille centre has been located at  the heart of Lille's university and scientific ecosystem, as well as at  the heart of Frenchtech, with a technology showroom based on Avenue de  Bretagne in Lille, on the EuraTechnologies site of economic excellence  dedicated to information and communication technologies (ICT).

Contexte et atouts du poste

This PhD student position will be supported by the HE Trumpet project, the HE Flute project and/or the PEPR IA Redeem project.    While this position will be in the MAGNET team in Lille, we will collaborate with the several European project partners.

While AI techniques are becoming ever more powerful, there is a growing concern about potential risks and abuses. As a result, there has been an increasing interest in research directions such as privacy-preserving machine learning, explainable machine learning, fairness and data protection legislation.
Privacy-preserving machine learning aims at learning (and publishing or applying) a model from data while the data is not revealed. Statistical privacy allows for bounding the amount of information revealed.

The MAGNET team is involved inthe related TRUMPET, FLUTE and REDEEM projects, and is looking for team members who can in close collaboration with other team members and national & international partners contribute to one or more of these projects.  All of these projects aim at researching and prototyping algoirhtms for secure, privacy-preserving federated learning in settings with potentially malicious participants.  The TRUMPET and FLUTE projects focus on applications in the field of oncology, while the REDEEM project has no a priori fixed application domain.



Mission confiée

The recruited PhD student will collaborate with colleagues in the MAGNET team and the project consortia in general.  Part of the work may involve travel to other partners.

If the research features a prototype, it will contribute to the project's open source library and may be supported by engineers in the team.

Possible domains of research include (but are not limited to):

  • Relevant topics in cryptography, statistics, distributed computing and programming languages
  • Design and development of the open source library


Principales activités

  • Contribute to the research of the TRUMPET, FLUTE and REDEEM projects
  • Collaborate with other MAGNET team members and project partners
  • Disseminate research results



The ideal candidate will have the following skills:

  • Good mastery of English
  • A strong background in computer science and mathematics.  Subject matters which will be needed during the research include (but are not limited to) machine learning, statistics, cryptography, distributed systems, constraint programming and programming languages.
  • Good programming skills (e.g., C/C++ or python) and supporting tools.
  • Relational skills, e.g., working in a team, effective reporting and communication with all involved stakeholders.


  • Subsidized meals
  • Partial reimbursement of public transport costs
  • Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
  • Possibility of teleworking and flexible organization of working hours
  • Professional equipment available (videoconferencing, loan of computer equipment, etc.)
  • Social, cultural and sports events and activities
  • Access to vocational training
  • Social security coverage


1st and 2nd year : 2100€ gross monthly salary (before taxes) 

3rd year : 2190€ gross monthly salary (before taxes)