Post-Doctorant F/H Numerical methods for high-dimensional problems

Context and Objective:

High dimensional problems are ubiquitous in many areas of science and engineering. Some examples are all the applications in which we have to perform uncertainty quantification, optimisation, or we have to deal with high-dimensional PDEs such as in kinetic theory or quantum mechanics. 

The goal of the project is to set up and investigate novel numerical methods to parsimoniously discretise high-dimensional problems. The goal is to introduce a notion of adaptivity in which the architecture of the approximation evolves dynamically on the basis of error and parsimony criteria. 

Assignments :
The recruited post-doc will actively participate to the research on the set up of numerical methods for high-dimensional problems. 

Collaboration :
The recruited person will be in connection with Damiano Lombardi, and will participate to the scientific discussions with collaborators in France and abroad.

Main activities (5 maximum) :

• Litterature review on adaptive tensor methods, neural networks methods for PDEs and hybrid approaches, as well as some pertinent results in approximation theory
• Start analysing novels ideas of adaptivity
• Study compression tasks as well as solving schemes for PDEs

• 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