Pour les employeurs
Research engineer in bioinformatics: inference of metabolic functions from metabarcoding data


Inria
il y a 3 jours
Date de publication
il y a 3 jours
S/O
Niveau d'expérience
S/O
Temps pleinType de contrat
Temps plein
A propos du centre ou de la direction fonctionnelle

The Centre Inria de l'Université de Grenoble groups together almost 600 people in 22 research teams and 7 research support departments.

Staff is present on three campuses in Grenoble, in close collaboration with other research and higher education institutions (Université Grenoble Alpes, CNRS, CEA, INRAE, ...), but also with key economic players in the area.

The Centre Inria de l'Université Grenoble Alpe is active in the fields of high-performance computing, verification and embedded systems, modeling of the environment at multiple levels, and data science and artificial intelligence. The center is a top-level scientific institute with an extensive network of international collaborations in Europe and the rest of the world.

Contexte et atouts du poste

The engineer will work within the framework of the European project HyLife ( https://hylife-cetp.com/ ) in the MICROCOSME team at Inria - Univ Grenoble Alpes. MICROCOSME is an interdisciplinary team that includes applied mathematicians, computer scientists, computational biologists as well as experimentalists from the microbiology/biophysics team BIOP of the Université Grenoble Alpes. The work will be carried out in collaboration with Arnaud Belcour, Hidde de Jong, and Delphine Ropers from MICROCOSME, as well as other members of the HyLife consortium from France, Germany, Norway and Czech Republic.

Mission confiée

Keywords : Bioinformatics, inference of metabolic function, environmental microbiology, energy storage

Title: Bioinformatics analysis of microbial risks associated with hydrogen underground storage in Europe

Context and motivation: The transition from fossil fuels to renewable energy sources is one of the most important steps to mitigate climate change and build a sustainable energy system. The conversion of excess energy from solar and winds plants into hydrogen gas (H2) is a promising solution that requires large-scale underground gas storage for later use. Underground storage sites-such as salt caverns, aquifers, and former gas reservoirs-naturally harbour microbial communities. Some microbes metabolize hydrogen and can convert it into toxic gases like hydrogen sulphide (H2S). These microbial activities could lead to H 2 losses and risks to operational safety and deterioration in H 2 quality [1]. To date there is little understanding of the mechanisms of microbial H 2 consumption and the effect of microbial growth on gas storage efficiency. The HyLife project aims to produce valuable insights into the types of microbes present and how they could influence stored H 2 through extensive sampling of potential storage sites all over Europe. Inferring the metabolic functions of microbial communities from taxonomic information could help characterize the microbial activity and estimate the associated risks. As a first step towards this goal, we have developed a pipeline called Tabigecy [2], which exploits taxonomic affiliations to predict metabolic functions constituting biogeochemical cycles and analyse their environmental impact in underground storage sites.

Description: The goal of the proposed work is to extend the Tabigecy pipeline towards hydrogen metabolism and to apply the pipeline to the samples obtained in the HyLife project. The ultimate objective is to map the metabolic functions of the sampled microbial communities onto biogeochemical cycles, and to evaluate the potential impact of these communities on H₂ in the various storage sites. One challenge is the lack of characterisation of microorganisms in the underground, as this affects the quality of predicted metabolic functions. Another challenge lies in the high computational cost of inferring metabolic functions due to the large number of samples (>100).

References:

[1] Dopffel, Jansen & Gerritse (2021). Microbial side effects of underground hydrogen storage-Knowledge gaps, risks and opportunities for successful implementation. International Journal of Hydrogen Energy , 46(12), 8594-8606.

[2] Belcour et al . (2025) Predicting coarse-grained representations of biogeochemical cycles from metabarcoding data. Bioinformatics , 41 (Supplement 1), i49-i57

Principales activités

The proposed project involves:
  • Understanding hydrogen metabolism from literature and textbooks
  • Extending the Python pipeline Tabigecy with new metabolic functions involved in hydrogen consumption and production
  • Applying Tabigecy to the numerous samples sequenced by the experimentalist partners of HyLife
  • Participating in reporting results, by helping to write articles and project deliverables and by communicating results to HyLife partners during on-line and on-site meetings.

Compétences

Good relational skills and English skills are important to work in an interdisciplinary and international environment.

Avantages

  • 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
Balises associées
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RÉSUMÉ DE L' OFFRE
Research engineer in bioinformatics: inference of metabolic functions from metabarcoding data
Inria
Montbonnot-Saint-Martin
il y a 3 jours
S/O
Temps plein

Research engineer in bioinformatics: inference of metabolic functions from metabarcoding data