Informations générales
Intitulé de l'offre : Polynomial optimization for network dynamics (fixed term researcher contract M/F) (H/F)
Référence : UPR8001-DIDHEN-002
Nombre de Postes : 1
Lieu de travail : TOULOUSE
Date de publication : mardi 4 novembre 2025
Type de contrat : Chercheur en contrat CDD
Durée du contrat : 24 mois
Date d'embauche prévue : 1 janvier 2026
Quotité de travail : Complet
Rémunération : Between €3041 and €3467 gross per month, depending on experience.
Niveau d'études souhaité : Doctorat
Expérience souhaitée : Indifférent
Section(s) CN : 07 - Sciences de l'information : traitements, systèmes intégrés matériel-logiciel, robots, commandes, images, contenus, interactions, signaux et langues
Missions
The project objective is to overcome the significant scalability barriers of the moment-sum-of-squares (moment-SOS) hierarchy, a powerful tool for solving non-linear, non-convex optimization problems.
Activités
The project will focus specifically on networked dynamical systems governed by nonlinear hyperbolic partial differential equations (PDEs). These models are crucial for applications like managing gas pipelines, traffic flow, and telecommunication networks. Our approach is to exploit the sparse network structure to decompose large-scale problems and leverage the theory of measure-valued solutions to handle the PDE dynamics without discretization.
The project will focus specifically on networked dynamical systems governed by nonlinear hyperbolic partial differential equations (PDEs). These models are crucial for applications like managing gas pipelines, traffic flow, and telecommunication networks. Our approach is to exploit the sparse network structure to decompose large-scale problems and leverage the theory of measure-valued solutions to handle the PDE dynamics without discretization.
Compétences
We are looking for a candidate with a PhD in Applied Mathematics, Control Theory, Optimization, or a related field. The position is flexible and can be tailored to the profiles:
- Analysis-Oriented: Strong theoretical background in functional analysis, measure theory, and convex optimization. Experience with the moment-SOS hierarchy. Expertise in PDE theory (especially hyperbolic conservation laws) is a significant plus.
- Computation-Oriented: Strong background in numerical methods for optimization, especially semidefinite programming (SDP). Experience with numerical linear algebra, polynomial bases, and code development (e.g., in Julia, Matlab, or Python). Knowledge of techniques for exploiting numerical structure (sparsity, low-rank) is highly desirable.
Contexte de travail
The MONET project is a bilateral collaboration between LAAS-CNRS (France) and FAU Erlangen-Nürnberg (Germany).
Le poste se situe dans un secteur relevant de la protection du potentiel scientifique et technique (PPST), et nécessite donc, conformément à la réglementation, que votre arrivée soit autorisée par l'autorité compétente du MESR.