Master’s internship: Verification of dynamic properties for a hybrid epidemic control model

Organisation/Company

Nantes Université

Department

LS2N

Research Field

Computer science » Modelling tools

Researcher Profile

First Stage Researcher (R1)

Country

France

Application Deadline

1 Feb 2024 – 00:00 (Europe/Paris)

Type of Contract

Other

Job Status

Full-time

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Context

In an international context marked by a constant increase in major epidemic events, scientific research is in great demand, in order to provide institutional players with decision-making support in a situation of urgency and uncertainty. Anticipating and controlling the spread of these emerging epidemics are two crucial issues that concern many scientific communities.

A great deal of progress has recently been made in modelling the dynamics of the spread of these events. To study the effect of human behaviour and the decisions of institutional players on biological dynamics, we know how to build hybrid models, by combining discrete probabilistic modelling tools such as Markov chains, derived from in-

formatics, with continuous deterministic modelling tools such as differential equations, derived from mathematics. Methods for verifying the properties of Markov chains are well known, as are methods for analysing the dynamics of differential equations. But the verification of the properties of these hybrid models obtained by coupling the two formalisms is a little-explored field, which today represents an essential area of research, with equally promising applications in other areas of the life sciences (study of the dynamic properties of biological systems).

Objectives of the internship

The main objective of this internship is to study the properties of a model of epidemiological dynamics, determined by a Markov decision process. This hybrid model is obtained by coupling a continuous deterministic process with a discrete probabilistic process, and should reproduce the juxtaposition of a continuous viral dynamic with a human decision-making dynamic. In addition to the usual properties such as the adequacy of the model to the observation data, the accessibility and invariance of the model equilibria, particular attention will be paid to dynamic properties such as the stability and periodicity of the trajectories. The verification methods used will be numerical and based on statistical processing of a set of model traces produced by numerical simulation. As the work progresses, symbolic verification methods associated with an algorithmic procedure may also be studied.

This internship will be carried out in the context of the CoSysM3 research project, led by Cristiana J. Silva (University of Lisbon, Portugal) and funded for 4 years by the Portuguese Science Foundation, which focuses on the control of epidemics.

Depending on the quality of the results obtained, and subject to funding being obtained, a PhD may be envisaged.

Candidate profile

To carry out this research work, the candidate will need solid skills in computer science, both theoretical (formal methods of model verification) and computational (digital simulation, intensive computing). The candidate should also have good writing skills and an aptitude for teamwork. Experience of studying epidemiological models would be highly appreciated.

Requirements

Research Field

Computer science » Other

Education Level

Master Degree or equivalent

Languages

ENGLISH

Level

Excellent

Additional Information
Work Location(s)

Number of offers available

1

Company/Institute

Nantes Université

Country

France

Geofield

Where to apply

E-mail

[email protected]

Contact

City

NANTES

Website

http://www.ls2n.fr

Street

1 QUAI DE TOURVILLE, BP 13522, 44035 NANTES CEDEX 01

STATUS: EXPIRED