Phd Position F/m Conformal Prediction and Physics-informed Machine Learning

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

**Type de contrat**: CDD

**Niveau de diplôme exigé**: Bac + 5 ou équivalent

**Fonction**: Doctorant

**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 research project is funded by the ANR project MELISSA (MEthodological contributions in statistical Learning InSpired by SurfAce engineering). In MELISSA, members are conducting research in statistical machine learning, following the constraints, the physical background knowledge and the observations of physical phenomena involved in repeated laser impacts on surfaces.

The hired PhD student will be based in the Inria Magnet team (Lille, France) and will be jointly supervised by Marc Tommasi, Batiste Le Bars and Pierre Humbert (CNRS, LaMME, Evry, France). Together, they gather a world-leading expertise in Machine Learning and Conformal Prediction. This project will stimulate existing and emerging collaborations with other research groups on themes at the intersection between machine learning, statistics and physics. For instance, there will be opportunities to collaborate with other members of the MELISSA project in Saint-Étienne (Laboratoire Hubert Curien, Teams MALICE, Data Intelligence and Laser-Matter interaction) and Sorbonne University (Laboratoire ISIR, MLIA Team).

**Mission confiée**:
During this PhD, we aim to develop Conformal Prediction (CP) methods in the context of Physics-informed Machine Learning (PiML). PiML has recently emerged as a promising way to learn efficient surrogate solvers for Partial Differential Equations (PDEs) and to learn prediction models using both real-data and the physical knowledge brought by a PDE.

**Principales activités**:
The tentative work-plan for this PhD is as follows:

- Consider the setting with performing CP with multiple models, and propose new methods for model selection using conformal prediction. Extend this to the PiML problem where we have access to several PDEs being uncertain.

**Compétences**:
The applicant is expected to have studied machine learning and/or statistics, and to have good mathematical skills. Some knowledge in optimization and physics, so as a broad interest for the topic of Physics-informed ML is a plus.

**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**:
2 200 € monthly gross salary

**Informations générales**:

- **Thème/Domaine**: Optimisation, apprentissage et méthodes statistiques
Calcul Scientifique (BAP E)
- **Ville**: Villeneuve d'Ascq
- **Centre Inria**: Centre Inria de l'Université de Lille
- **Date de prise de fonction souhaitée**: 2025-10-01
- **Durée de contrat**: 3 ans
- **Date limite pour postuler**: 2025-09-01

**Consignes pour postuler**:
Please send your CV and cover letter

**Sécurité défense**:
Ce poste est susceptible d’être affecté dans une zone à régime restrictif (ZRR), telle que définie dans le décret n°2011-1425 relatif à la protection du potentiel scientifique et technique de la nation (PPST). L’autorisation d’accès à une zone est délivrée par le chef d’établissement, après avis ministériel favorable, tel que défini dans l’arrêté du 03 juillet 2012, relatif à la PPST. Un avis ministériel défavorable pour un poste affecté dans une ZRR aurait pour conséquence l’annulation du recrutement.

**Politique de recrutement**:
Dans le cadre de sa politique diversité, tous les postes Inria sont accessibles aux personnes en situation de handicap.

**Contacts**:

- **Équipe Inria**: MAGNET
- **Directeur de thèse**:
**A propos d'Inria**:
Inri