PhD thesis No. 3 of the EXPERT Nexus: « Mesoscale mathematical modelling of bacterial persistence»

Updated: 9 days ago
Location: Montpellier, LANGUEDOC ROUSSILLON
Job Type: FullTime
Deadline: 20 May 2026

27 Mar 2026
Job Information
Organisation/Company

Universite de Montpellier
Department

Human Resources
Research Field

Biological sciences » Biology
Researcher Profile

First Stage Researcher (R1)
Positions

PhD Positions
Application Deadline

20 May 2026 - 23:59 (Europe/Paris)
Country

France
Type of Contract

Temporary
Job Status

Full-time
Offer Starting Date

1 Oct 2026
Is the job funded through the EU Research Framework Programme?

Other EU programme
Reference Number

2026-D0015
Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

- work environment: The proposed PhD thesis forms part of the Nexus network, which comprises five researchers and three PhD students working on a shared theme: ‘The microbial EXposome and the determinants of persistent infections in humans: an interdisciplinary approach to understanding the interaction between bacterial pathogens of environmental and zoonotic origin and the host’s innate immune system. ” In this thesis, we will develop structured partial differential equation models of bacterial persistence. A particular challenge, both for simulation and for machine learning, lies in the high dimensionality of these equations, which causes grid-based numerical methods to fail and necessitates the development of new approaches.

- main mission: Develop and analyze structured partial differential equations models to investigate the mechanisms driving bacterial persistence in chronic infections (Salmonella, Pseudomonas, and Achromobacter) by integrating spatial modelling, single-cell transcriptomics, advanced imaging data, and machine learning approaches. The goal is to identify common and pathogen-specific mechanisms of persistence and to generate quantitative predictions supporting experimental studies.

- activities: 

  • Develop three pathogen-specific mesoscale models based on structured partial differential equations (PDEs).
  • Construct a unified modelling framework describing:
    • Spatial tissue dynamics (gradients, chemotaxis, cell–cell interactions).
    • Macrophage polarization (M1–M2 continuum and activation states).
    • Bacterial phenotypic heterogeneity (replication, dormancy, intracellular survival).
  • Integrate single-cell transcriptomic data to build molecular dynamical models of macrophage polarization and host response.
  • Incorporate quantitative microscopy data to estimate parameters related to:
    • Bacterial localization (intra-/extracellular),
    • Replication dynamics,
    • Infected macrophage populations.
  • Perform parameter estimation using optimization and machine learning approaches
  • Develop numerical schemes for high-dimensional structured PDEs (pseudospectral methods, meshfree/particle approaches).
  • Conduct sensitivity analysis and model reduction to identify key drivers of persistence.
  • Use models to simulate in silico scenarios (immune modulation, relapse, clearance vs persistence thresholds).

 

The gross monthly salary is €2,300

Contract duration: 3 years

Contract date from 01/10/2026 to 30/09/2029


Where to apply
E-mail

ovidiu.radulescu@umontpellier.fr

Requirements
Research Field
Biological sciences » Biology
Education Level
Master Degree or equivalent

Research Field
Mathematics » Applied mathematics
Education Level
Master Degree or equivalent

Research Field
Physics
Education Level
Master Degree or equivalent

Skills/Qualifications

Essential 

  • Strong background in applied mathematics, mathematical biology, or computational modelling.
  • Experience with partial differential equations (PDEs) and dynamical systems.
  • Programming skills (Python, MATLAB, or equivalent).
  • Interest in quantitative modelling of biological systems.
  • Ability to work with interdisciplinary data (omics and imaging). 

Desirable 

  • Experience with:
    • Structured population models,
    •  Multiscale modelling,
    • Numerical analysis of PDEs,
    • Machine learning for parameter inference,
    • Model calibration and sensitivity analysis.
  • Familiarity with systems biology, immunology, or host–pathogen interactions.
  • Experience handling transcriptomic or imaging datasets.
  • Strong scientific writing and communication skills. 

Diploma/field required: Master 2 / Applied Mathematics, Computational Physics, Computational Biology


Additional Information
Selection process

The application must include the following 

  • A CV
  • A motivation letter
  • One or two letters of recommendation.
  • The most recent transcripts from Master 1 and Master2 (semester 1 and/or semester 2)
  • Names and coordinates of 2 referees

If you would like to apply for this position, please send an e-mail to the thesis director Ovidiu Radulescu mailto:ovidiu.radulescu@umontpellier.fr+ co-director Anne Blanc-Potard anne.blanc-potard@umontpellier.fr , and exposum-aap@umontpellier.fr to inform them of your interest.

Application deadline: Before 20 May 2026.

Website Link :  https://www.umontpellier.fr/articles/exposum-doctoral-nexus-sujets-de-t…


Work Location(s)
Number of offers available
1
Company/Institute
Laboratory of Pathogens and Host Immunity (LPHI)
Country
France
Geofield


Contact
City

Montpellier
Website

http://www.umontpellier.fr/
Street

163 rue Auguste Broussonnet
Postal Code

34000

STATUS: EXPIRED

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