2022-05012 - Engineer - Scientific programmer in trustworthy multi-site privacy-preserving technologies (F/M)
Le descriptif de l’offre ci-dessous est en Anglais

Type de contrat : CDD

Niveau de diplôme exigé : Bac + 5 ou équivalent

Fonction : Ingénieur scientifique contractuel

Niveau d'expérience souhaité : Jusqu'à 3 ans

A propos du centre ou de la direction fonctionnelle

The Inria Lille - Nord Europe Research Centre was founded in 2008 and employs a staff of 320, including 280 scientists working in fourteen research teams. Recognised for its outstanding contribution to the socio-economic development of the Hauts-De-France région, the Inria Lille - Nord Europe Research Centre undertakes research in the field of computer science in collaboration with a range of academic, institutional and industrial partners.

 The strategy of the Centre is to develop an internationally renowned centre of excellence with a significant impact on the City of Lille and its surrounding area. It works to achieve this by pursuing a range of ambitious research projects in such fields of computer science as the intelligence of data and adaptive software systems. Building on the synergies between research and industry, Inria is a major contributor to skills and technology transfer in the field of computer science.

Contexte et atouts du poste

This engineer position will be supported by the HE Trumpet 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. Notions such as (local) differential privacy and its generalizations allow to bound the amount of information revealed.

The overall goal of the TRUMPET project is to research and develop novel privacy enhancement methods for Federated Learning, and to deliver a highly scalable Federated AI service platform for researchers, that will enable AI-powered studies of siloed, multi-site, cross-domain, cross-border European datasets with privacy guarantees that exceed the requirements of GDPR. 

INRIA's MAGNET team will contribute among others to tasks involving AI algorithms and architectures, federated Learning, privacy platforms, privacy measurement and metrics, privacy-enhancing technologies and applied cryptography

 

Mission confiée

The recruited engineer will collaborate with colleagues in the MAGNET team and the TRUMPET project consortium.  In particular, the work will contribute to TRUMPET's platform, by collaboratively designing and developing the overall architecture and contributing modules providing privacy enhancing technologies (PETs) and privacy assessment functionality based on MAGNET scientific advances

By default all developed software will be open-source.

 

Principales activités

  • Studying new algorithms for reasoning about data privacy
  • Design and prototyping of key algorithms
  • Create appropriate documentation
  • Integrate such implementations in the TRUMPET platform
  • test algorithms and run experiments

 

Compétences

Technical skills and level required :

  • a strong understanding of algorithms
  • software design and development skills (relevant code may include Python and/or C/C++)
  • understanding of process models and (probabilistic) reasoning techniques

Languages :

  • Mastering English is essential

Relational skills :

  • smoothly working in a team in a reseach environment
  • effective communication and collaboration

Avantages

  • 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

Rémunération

According to the profile