Polynomial optimization for network dynamics (fixed term researcher contract M/F)

Job Description

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.

Activity

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.

Your Profil

Skills

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.

Your Work Environment

The MONET project is a bilateral collaboration between LAAS-CNRS (France) and FAU Erlangen-Nürnberg (Germany).

Compensation and benefits

Compensation

Between €3041 and €3467 gross per month, depending on experience.

Annual leave and RTT

44 jours

Remote Working practice and compensation

Pratique et indemnisation du TT

Transport

Prise en charge à 75% du coût et forfait mobilité durable jusqu’à 300€

About the offer

About the CNRS

The CNRS is a major player in fundamental research on a global scale. The CNRS is the only French organization active in all scientific fields. Its unique position as a multi-specialist allows it to bring together different disciplines to address the most important challenges of the contemporary world, in connection with the actors of change.

CNRS

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