ORGANISATION/COMPANYGrenoble INP / Université Grenoble Alpes, laboratoire Jean Kuntzmann
RESEARCH FIELDComputer science › Digital systemsComputer science › InformaticsMathematics
RESEARCHER PROFILEFirst Stage Researcher (R1)Recognised Researcher (R2)Established Researcher (R3)Leading Researcher (R4)
APPLICATION DEADLINE30/06/2021 00:00 - Europe/Brussels
LOCATIONFrance › Saint Martin d'Hères
TYPE OF CONTRACTTemporary
OFFER STARTING DATE01/10/2021
The PhD project aims to understand the dynamics and themost determining parameters in the propagation of Covid-19, to propose epidemic control strategies in termsof containment policies, testing campaigns or vaccination, with the Auvergne-Rhône-Alpes territory as a study framework. For this purpose, we propose an original approach to the modeling of epidemic dynamics based on the development of a 3D advection-diffusion-reaction distributed parameter model (2 spatial dimensions and one age-related dimension) and the use of model reduction techniques, potentially avoiding the pitfall of over-parameterization of traditional SIR models. It is important to emphasize that the scientific approach we propose is generic and could be transposed to the study of pandemics on different geographical entities or to other epidemic transmission dynamics, or even to other application domains involving complex and potentially non-linear dynamics on a heterogeneous environment. The scientific challenges of this project are multiple : modeling of non-linear distributed phenomena on a complex 3D heterogeneous medium, assimilation of uncertain and heterogeneous data leading to ill-posed inverse problems, high dimensional optimal control problems. The PhD student will be supervised by Clémentine Prieur (LJK, UMR 5224) and Didier Georges(GIPSA-lab, UMR 5216) and attached to the LJK. The modeling stage will involve informed exchanges with E. Vergu (INRAE), expert in epidemiology and modeling, and R. Sameni (Univ. Emory, Atlanta), expert in
modeling and compartmental systems analysis. A provisional schedule for the thesis is :
— Year 1 : bibliographical study on modeling in epidemiology, sensitivity analysis, model reduction and
numerical solution of non-linear systems governed by partial differential equations, inverse problems
and optimal control ; modeling and simulation of the epidemiological model ; construction and analysis
of a reduced model ; first valorization of the results ;
— Year 2 : sensitivity analysis, formulation and resolution of the inverse problem using a moving horizon
approach ; evaluation of the results ;
— Year 3 : formulation and resolution of an epidemic control problem based on the developed model ;
finalization of publications, writing and defense of the thesis.
The project will benefit from the technical support of P. Bellemain (IE CNRS) for data collection and
processing, as well as for the development of a simulator and the implementation of the algorithms developed
in the framework of the project. We already have privileged access to the data of the COVID-19 platform of
the French Ministry of Health. We will also have access
Funding category: Contrat doctoral
PHD title: Doctorat de Mathématiques Appliquées
PHD Country: France
Master level or equivalent in applied mathematics, skills in numerical solving for PDEs, in optimization and analysis of dynamical systems, skills and taste for programming (e.g. in Python, R, Matlab, Julia or C/C++. . . ).
EURAXESS offer ID: 630139
Posting organisation offer ID: 97612
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