Phd Position F - M Being Exposed Only To The Risks I Am Willing To Take H/F INRIA

PhD Position F/M Being exposed only to the risks I am willing to take
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : CDD

Contrat renouvelable : Oui

Niveau de diplôme exigé : Bac +5 ou équivalent

Fonction : Doctorant

A propos du centre ou de la direction fonctionnelle

The Inria Grenoble research center groups together almost 600 people in 25 research teams and 8 research support departments.

Staff is present on three campuses in Grenoble, in close collaboration with other research and higher education institutions (University Grenoble Alpes, CNRS, CEA, INRAE, ...), but also with key economic players in the area.

Inria Grenoble is active in the fields of high-performance computing, verification and embedded systems, modeling of the environment at multiple levels, and data science and artificial intelligence. The center is a top-level scientific institute with an extensive network of international collaborations in Europe and the rest of the world.

Contexte et atouts du poste

Context.This PhD thesis is part of the MIAI Chair RAIDAC+ (Responsible AI: Design, Regulation, and Conformity), coordinated by Héber H. Arcolezi and Theodore Christakis. RAIDAC+, which started in September 2025,is a transdisciplinary initiative that integrates pioneering research in AI privacy, fairness, transparency, and robustness with cutting-edge expertise in AI regulation, law, and policy

The thesis will be conducted under a co-tutelle agreement between Inria Grenoble (France) and ÉTS Montreal (Canada), leveraging the complementary strengths of both institutions.

The envisioned plan is for the recruited PhD student to spend approximately two years at Inria Grenoble (Privatics team), followed by two years at ÉTS Montreal. This structure will provide a rich and balanced international training environment, enabling the student to benefit from diverse expertise, ecosystems, and research cultures.

The thesis will be co-supervised by:

- , Researcher at Inria and incoming Assistant Professor at ÉTS Montreal (February 2026).
- , Associate Professor at INSA Lyon.
- , Assistant Professor at ÉTS Montreal.

The PhD project will contribute to the core objectives of RAIDAC+, with a particular focus on advancing methodologies that jointly address privacy risk explainability. The student will also benefit from the broader international collaborations and mobility opportunities enabled by the co-tutelle agreement, further strengthening the international dimension of their training and research.

Mission confiée

Assignment.Effectively protecting personal data is challenging. A large number of protection mechanisms have been proposed in the academic literature but very few have been adopted by application providers and companies in the field and even fewer by users. Furthermore, protecting data inherently also comes with a loss of service and utility (i.e., there is no free food). Data anonymization is rarely perfect, we are talking more about the probability of risk depending on the means used by an adversary to carry out a re-identification attack (e.g., collection of auxiliary information, etc.). The risk is necessarily greater for atypical people than for people more similar to the rest of the population.

However, before asking the question of how to effectively protect our location data and what risk remains, perhaps it is better to ask whether it is relevant to generate this data and let third parties collect it. Indeed, without collected personnal data, the risk of disclosing information in an uncontrolled manner does not exist. Raising user awareness by better explaining the risks would reduce the amount of data generated and collected. In this context, this PhD thesis will revisit the explanation mechanisms, often used to technically explain to designers the key factors of a decision, to better explain to end users which information generates more or less risk. By being fully aware of the risk, the user can choose in full knowledge, if he wishes to disclose such or such information.

Research Objective.The goal is therefore to develop explainable mechanisms to 1) clearly inform end users about the different risks of inference, and 2) give the user control what risk is acceptable or not to them. If the user does not want to expose themselves to a certain risk, the data must be cleaned or sanitized to eliminate this risk of inference.

Principales activités

Main activities:

- Carry out the PhD research project on privacy risk explainability.
- Collaborate with other team members and with project partners (e.g., UQAM, Federal University of Ceará, Inria, ÉTS Montréal).
- Disseminate research results through publications and presentations at international conferences.

Compétences

We are looking for a candidate with:

- Good programming skills in Python and good analytical skills.
- A good background in probability/statistics and deep learning is expected.
- Knowledge of differential privacy and/or fairness is a plus, but not necessary.
- The candidate should be fluent in English.

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 (90 days / year) 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
- Complementary health insuranceunder conditions

Rémunération

2200euros gross salary / month