Dynamics of competing microbial consortia in the context of underground hydrogen storage: a combined experimental and modelling approach

With the development of underground hydrogen storage, it is becoming increasingly important to anticipate how microbial communities will evolve and interact with injected H₂. This PhD project aims to develop a mechanistic model of microbial competition in hydrogen-rich subsurface environments. The work will combine laboratory batch experiments, modeling of microbial consortiums dynamics, and simulations under realistic underground storage conditions.
The first phase will consist in investigating the behavior of two microbial strains with contrasting metabolisms (methanogenic and iron-reducing) under controlled conditions and at different temperatures. The second will focus on designing a generic model that accounts for trophic and inhibitory interactions, as well as environmental constraints (resources, temperature, …). Finally, the model will be applied to simulate subsurface scenarios, helping to assess microbial stability, resilience, or potential drifts.
This PhD project adopts an interdisciplinary approach combining microbiology, physico-chemistry, biogeochemistry and modeling to understand the fate of hydrogen in the context of subsurface storage in porous media.

Keywords: Environmental microbiology, microbial consortia, biological modelling, microbial competition, underground hydrogen storage, batch experiments

• Academic supervisor    Pr. François Guyot, MNHN Paris, ORCID : 0000-0003-4622-2218
• Doctoral School    ED227 DIVONA, Sorbonne Université
• IFPEN supervisor    Dr. Arnaud PUJOL, arnaud.pujol@ifpen.fr, ORCID : 0000-0002-0611-5832
• PhD location    IFPEN, Rueil-Malmaison, France  
• Duration and start date    3 years, starting in the fourth quarter 2026
• Employer    IFPEN
• Academic requirements    University Master degree in microbiology, microbial ecology, biogeochemistry or systems biology    
• Language requirements    English level B2 (CEFR)  
• Other requirements    Interest in scientific modeling and coding (Python). Experience in biological dynamics or batch experimentation is a plus. The candidate should be autonomous, rigorous, and curious
• Other information    Collaboration and experimentations at Paris-Saclay University

To apply, please send your cover letter and CV to the IFPEN supervisor indicated here below.