Post-Doctoral Research Visit F - M Bayesian Inference With Sources Of Uncertainty From Confidence Modelling To Sparse Estimation H/F

INRIA

Post-Doctoral Research Visit F/M Bayesian inference with sources of uncertainty: from confidence modelling to sparse estimation
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : CDD

Niveau de diplôme exigé : Thèse ou équivalent

Fonction : Post-Doctorant

A propos du centre ou de la direction fonctionnelle

The Centre Inria de l'Université de Grenoble groups together almost 450 people in 26 research teams and 9 research support departments.

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

The Centre Inria de l'Université Grenoble Alpes 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

The Inria Grenoble research center groups together almost 600 people in 27 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.

Mission confiée

We aim to introduce a general framework that extends Bayesian inference by allowing the researcher to explicitly encode confidence in each source of uncertainty within the model. This mechanism will provide a new handle for model design and regularisation control. Building on this framework, we will develop a general approach for inducing sparsity in statistical models and illustrate its use in linear and logistic regression, as well as in Bayesian neural networks.

Collaboration :
The recruited person will be in connection with Julyan Arbel and Florence Forbes.

Responsibilities :
The person recruited is responsible fordevelopping the new SoU framework, and will take initiatives forcollaboration and co-supervision.

Principales activités

Main activities:

Studying literature

Implementing and testing models

Writing research reports

Presenting results to conferences

Compétences

Technical skills and level required :

Languages :

Relational skills :

Other valued appreciated :

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

2788 euros gross salary per month