Post-Doctoral Research Visit F/M Inference of a demo-genetic model for sustainable plant resistance

European Commission; France; Sur place; EUR 35 000 - 45 000; Plein temps

Résumé du poste

Un institut national de recherche en sciences numériques recherche un postdoctorant pour un projet innovant visant à étudier la durabilité des cultures résistantes aux maladies. Le candidat travaillera sur des modèles épidémiologiques en collaboration avec des équipes interdisciplinaires, en utilisant des méthodes avancées de simulation et d'inférence. Une bonne maîtrise de la programmation, en particulier en C++, est essentielle, tout en favorisant une communication efficace avec les partenaires du projet.

Prestations

Remboursement partiel des frais de transport

7 semaines de congés annuels + 10 jours RTT

Possibilité de télétravail

Équipement professionnel (vidéoconférence, prêt d'ordinateur)

Accès à la formation professionnelle

Qualifications

• Expertise en inférence basée sur les simulations.
• Intérêt marqué pour les applications biologiques et motivation pour le travail interdisciplinaire.
• Bonnes compétences en communication pour assurer une collaboration fluide.

Responsabilités

• Adapter le modèle pour inclure migration et coûts de virulence.
• Développer une méthode pour estimer les paramètres du modèle à partir de données historiques.
• Concevoir des stratégies durables pour le déploiement de résistances multiples.

Connaissances

Dynamique des populations

Programmer en C++

Méthodes d'inférence

Modélisation numérique

Analyse de sensibilité

Formation

Doctorat en biologie ou domaine connexe

Description du poste

Inria, the French national research institute for the digital sciences

Organisation/Company Inria, the French national research institute for the digital sciences Research Field Mathematics Researcher Profile Recognised Researcher (R2) Country France Application Deadline 30 Sep 2025 - 00:00 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 38.5 Offer Starting Date 1 Nov 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 2025-08745 Is the Job related to staff position within a Research Infrastructure? No

Offer Description

This postdoctoral position if funded by the ANR (French National Research Agency) ENDURANCE ENhanced DURability AgaiNst Crop Enemies project, which brings together partners from INRAE and Inria. This interdisciplinary project combines molecular biology, population genetics, and epidemiological modelling, to determine optimal deployment strategies for plant resistance.

The postdoctoral fellow will join the MACBES team (Inria, INRAE, CNRS, Université Côte d'Azur) in Sophia Antipolis and will closely collaborate with Suzanne Touzeau (MACBES & M2P2 teams) and Florence Carpentier (AgroParisTech & MaIAGE, INRAE) based near Paris.

The postdoctoral fellow will interact with other ENDURANCE partners and the M2P2 team at ISA (INRAE, CNRS & Université Côte d'Azur).

Crop protection often remains dependent on chemical pesticides, which are both harmful for the environment and human health. Resistant crops are an agroecological alternative to pesticides, but their extensive use may lead to the emergence/selection of virulent pathogens and resistance breakdown. Devising deployment strategies of resistant crops that are both efficient, i.e. that reduce crop damages, and durable, i.e. that limit the virulent pathogen populations, is hence a major issue.

The postdoctoral fellow will tackle this issue by means of a demo-genetic model, tailored for a specific pathosystem, the phoma stem canker of oilseed rape caused by fungus Leptosphaeria maculans. The emergence and development of virulent pathogens may vary according to the genetic determinisms of virulence (molecular mechanisms responsible for the transition to virulence, epistatic interactions, fitness costs), which are studied by other partners of the ENDURANCE project.

The work will be based on:

• time-series data of (i) phoma populations and resistance breakdowns, as well as (ii) resistance deployment in oilseed rape crops;
• a stochastic, discrete-time epidemiological model of an haploid monocyclic fungal pathogen, which includes features of the oilseed rape stem canker, such as interactions between resistance and avirulence genes;
• the corresponding C++ code.

The objectives of this position are threefold:

• adapt the model to take into account migration, mutation, and pathotype-dependent virulence costs, based on recent advances in the genetic determinisms of virulence;
• develop a method to estimate model parameters from historical data, in order to gain deeper insights into the observed dynamics of resistance breakdown;
• devise durable strategies for the deployment of multiple resistances.

Generic activities include: literature review, data processing, reporting, paper writing, participation and presentation in project meetings and in relevant conferences.

Specific activities include:

• programming and numerical simulations (using a computing cluster),
• inference based on simulations (ABC-like method),
• numerical exploration (sensitivity analysis) and optimisation.
• Background in population dynamics and/or population genetics.
• Expertise in inference and/or optimisation.
• Experience in programming, preferably in C++.
• Knowledge of plant epidemiology would be a plus.
• Proficiency in written and spoken English.

Specific Requirements

• Expertise in simulation-based inference.
• Marked interest in biological applications and motivation for interdisciplinary work.
• Good communication skills to ensure a smooth collaboration with Florence Carpentier.

Languages FRENCH Level Basic

Languages ENGLISH Level Good

Additional Information

• 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
• Contribution to mutual insurance (subject to conditions)