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Candidature spontanée

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Réf. : 04

Postdoctorant.e

Le CBGP recherche un postdoctorant.e pour une durée de 18 mois à partir d'octobre 2024.

Development of statistical methods for the reconstruction of routes of biological invasion: inference of complex evolutionary scenario from genomic data using admixture graphs

Admixture graphs (AG) describe the demographic history of a set of populations as a directed acyclic graph that represents population splits and merges. They are particularly useful in studying biological invasions, as they can model the recent introduction history of individuals from native and invasive population samples. AGs have great, as yet unexplored, potential for selecting a set of (most probable) invasion scenarios from large-scale population polymorphism data (obtained from the entire genome of the organisms under study). AGs can be inferred using statistical methods that employ simplified models of evolution based on allele frequency covariances between population samples. The selected graphs can then be exploited by more sophisticated methods, that use complex models and likelihood free inference techniques for model choice, parameter estimation, or goodness of fit. The inference of AGs is an active field of research, with recent methods based on maximum likelihood or Bayesian approaches. Because these methods need to explore the huge space of possible graphs, they are subject to a number of algorithmic and mathematical challenges. The aim of the post-doctoral project is to study the behaviour of these methods on simulated and real datasets (mainly full-genome polymorphism data for a large number of population samples from two invasive insect species), and, based on the results, to propose new improved statistical methods. Possible lines of research could include i) the integration of uncertainty in the estimation of the covariance of population allele frequencies and its adaptation to more complex data (e.g., Pool-Seq data); ii) the exploration of the AG space and the resolution of identifiability issues, using the related but distinct literature on phylogenetic networks; and iii) the improvement of model choice approaches to compare AGs (e.g. via likelihood-based scores).

Useful references:

Gautier et al. 2022. https://doi.org/10.1111/1755-0998.13557

Maier et al. 2023. https://elifesciences.org/articles/85492

Nielsen et al. 2023. https://doi.org/10.1371/journal.pgen.1010410

Rhodes et al. 2024+ https://arxiv.org/abs/2402.11693

Main PIs: Arnaud Estoup and Mathieu Gautier (Biology and Population Genomics; INRAE Montpellier, France), Cécile Ané (Maths-Stat; University of Wisconsin-Madison, USA), Paul Bastide (Maths-Stat; CNRS, MAP5, University of Montpellier and soon at University of Paris Cité, France), Jean-Michel Marin (Maths-Stat; University of Montpellier, France).

Application deadline: September 15th, 2024.

Salary: > 2650 € per month (after taxes; cf. ca. > 3100 € before taxes) depending on post-PhD experience.

Timing: position available from October 2024 with a starting date between October 2024 and March  2025 (Phd degree obtained before taking up the position).

Note: The Post-Doc will have the opportunity to spend a few months at the University of Wisconsin-Madison, USA (cf. co-supervision with Cécile Ané)

Other information related to the position: The aim of the Centre de Biologie pour la Gestion des Populations is to understand the mechanisms that govern the evolution of populations of organisms that are important for agronomy, forestry, human health or the conservation of biodiversity.

Montpellier is a major hotspot for evolutionary and environmental research worldwide and has a vibrant research community with several hundred researchers in this domain, and highly praised graduate programs. The University of Montpellier is top ranked in the Shanghai ranking in Ecology. Montpellier lies near the Mediterranean region in the South of France and enjoys pleasant weather, fantastic nature and great cultural and city life. For information on the cost of living in Montpellier, France, you can consult the following websites:

  • Numbeo: This is probably the most comprehensive site for cost of living comparisons between cities. It offers details of the cost of food, housing, transport, etc., based on user contributions.
  • Expatistan: Another useful site that provides an overview of the cost of living in different cities, including Montpellier. It is also based on user contributions. (expatistan.com)
Type de poste

Postdoctorant.e, 18 mois.

Application and contact:

A PhD in statistics / population genetics or relevant field is expected. Informal enquiries are highly encouraged.

Please contact Arnaud Estoup (arnaud.estoup@inrae.fr). Formal application includes a letter of application with details on the motivation, a full CV, the names and contact details of two references, and the date of availability.

Réf. : 03

Doctorant.e

Le CBGP recherche un doctorant.e pour une thèse de 3 ans à partir de septembre 2024.

Genomic prediction of adaptation: statistical developments and application to an invasive species of crop pest, Drosophila suzukii

Key words: Hierarchical Bayesian Models, Deep learning, Population genomics, Adaptation, Genomic Prediction, Drosophila suzukii

Summary: By combining genomic and environmental data obtained on a wide range of populations assumed to be locally adapted, one can learn which alleles influence the adaptation to a given environment and, thus, predict the adaptive potential of a genotyped target population to a given new environment. One important application of this approach is to predict the risk represented by a population of a (pest) species of interest in a given environment, especially the risk of establishment of an invasive population in a new geographical area according to its present (or future) climate, the potential damage caused on a given host plant, or the ability to resist control methods. Hierarchical Bayesian Model (HBM) and Random Forests are potential statistical approaches that have already been used in this context. During this PhD, particular attention will be paid to the Baypass method (Gautier 2015), currently used to detect loci that facilitate adaptation to an environmental variable, as it can be extended to predictive tasks. The Baypass modelling framework is based on Bayesian linear models. It has the important property of accounting for population spatial structure, which is an important confounder in this context. However, this approach assumes a linear relationship between allele frequencies and environmental variables and does not explicitly models interactions between loci. Therefore, alternative approaches based on neural networks will be considered, as they are able to capture more complex associations between the genome and the environment and are well suited for the analysis of high-dimensional heterogeneous data. To compensate for the small number of observations that generally characterize population genomic prediction studies (an observation here being a population), it would be worth to implement so-called hybrid-AI methodologies by integrating additional information, for example on the structure or annotation of the genome, which is well known for some pest species. Finally, it would be worthwhile to explore frugal AI approaches that would allow the training set to be expanded to include unlabelled samples (i.e. populations for which the phenotype or environment has not been measured).

Profile and skills: This interdisciplinary project will involve concepts from population genetics, statistics and machine learning. Strong background in at least one of the three first fields is expected. A large part of the work will be devoted to the analysis and simulation of high throughput genomic data, which requires strong interest in modelling, computational approaches and programming.

Funding: A 3 years PhD grant is available from September 2024 through the target project “Agrostat” of the PEPR “MathsVives”.

Type de poste

Doctorant.e, 3 ans.

Application and contact:

To apply to this position, please send a CV and a motivation letter at the two contact persons below:

Réf. : 02

Ingénieur·e en calcul scientifique

Un poste d'ingéneur·e de recherche INRAE devrait bientôt être ouvert au CBGP !

Le CBGP devrait prochainement proposer un poste permanent d’ingénieur.e de recherche, spécialisé dans l’inférence et la prédiction en génomique des populations.

De nombreux projets de recherche au CBGP reposent sur l’utilisation de méthodes computationnelles développées dans l’unité pour comprendre l’histoire évolutive des populations de ces espèces et anticiper leurs dynamiques futures. Votre mission serait de participer au développement et à l’application d’approches d’inférence et de prédiction en génomique des populations, en utilisant des méthodes et des outils de l’intelligence artificielle.

Pour plus d’informations concernant le profil et pour postuler, rendez-vous sur le site INRAE Jobs dès le 21/02/2024. Et si vous voulez recevoir une notification par mail le jour J, n’hésitez pas à créer une alerte emploi.

Type de poste

Concours externe des ingénieurs, cadres et techniciens (H/F) INRAE

Contact

Pour plus d’informations, veuillez contacter Raphaël Leblois ou Renaud Vitalis

Réf. : 01

Technicien·ne en expérimentation animale

Un poste de technicien·ne de recherche INRAE devrait bientôt être ouvert au CBGP !

Le CBGP devrait prochainement proposer un poste permanent de technicien·ne de recherche en expérimentation animale, spécialisé en élevage et phénotypage haut-débit d’insectes phytophages. Ces activités sont développées au sein d’un collectif de chercheur·e·s, ingénieur·e·s et technicien·ne·s regroupés sur un plateau technique dédié à l’élevage et au phénotypage d’arthropodes.

Pour plus d’informations concernant le profil et pour postuler, rendez-vous sur le site INRAE Jobs dès le 21/02/2024. Et si vous voulez recevoir une notification par mail le jour J, n’hésitez pas à créer une alerte emploi.

Type de poste

Concours externe des ingénieurs, cadres et techniciens (H/F) INRAE

Contact

Pour plus d’informations, veuillez contacter Julien Foucaud ou Carole Kerdelhué

Réf. : 04

Postdoctorant.e

Le CBGP recherche un postdoctorant.e pour une durée de 18 mois à partir d'octobre 2024.

Development of statistical methods for the reconstruction of routes of biological invasion: inference of complex evolutionary scenario from genomic data using admixture graphs

Admixture graphs (AG) describe the demographic history of a set of populations as a directed acyclic graph that represents population splits and merges. They are particularly useful in studying biological invasions, as they can model the recent introduction history of individuals from native and invasive population samples. AGs have great, as yet unexplored, potential for selecting a set of (most probable) invasion scenarios from large-scale population polymorphism data (obtained from the entire genome of the organisms under study). AGs can be inferred using statistical methods that employ simplified models of evolution based on allele frequency covariances between population samples. The selected graphs can then be exploited by more sophisticated methods, that use complex models and likelihood free inference techniques for model choice, parameter estimation, or goodness of fit. The inference of AGs is an active field of research, with recent methods based on maximum likelihood or Bayesian approaches. Because these methods need to explore the huge space of possible graphs, they are subject to a number of algorithmic and mathematical challenges. The aim of the post-doctoral project is to study the behaviour of these methods on simulated and real datasets (mainly full-genome polymorphism data for a large number of population samples from two invasive insect species), and, based on the results, to propose new improved statistical methods. Possible lines of research could include i) the integration of uncertainty in the estimation of the covariance of population allele frequencies and its adaptation to more complex data (e.g., Pool-Seq data); ii) the exploration of the AG space and the resolution of identifiability issues, using the related but distinct literature on phylogenetic networks; and iii) the improvement of model choice approaches to compare AGs (e.g. via likelihood-based scores).

Useful references:

Gautier et al. 2022. https://doi.org/10.1111/1755-0998.13557

Maier et al. 2023. https://elifesciences.org/articles/85492

Nielsen et al. 2023. https://doi.org/10.1371/journal.pgen.1010410

Rhodes et al. 2024+ https://arxiv.org/abs/2402.11693

Main PIs: Arnaud Estoup and Mathieu Gautier (Biology and Population Genomics; INRAE Montpellier, France), Cécile Ané (Maths-Stat; University of Wisconsin-Madison, USA), Paul Bastide (Maths-Stat; CNRS, MAP5, University of Montpellier and soon at University of Paris Cité, France), Jean-Michel Marin (Maths-Stat; University of Montpellier, France).

Application deadline: September 15th, 2024.

Salary: > 2650 € per month (after taxes; cf. ca. > 3100 € before taxes) depending on post-PhD experience.

Timing: position available from October 2024 with a starting date between October 2024 and March  2025 (Phd degree obtained before taking up the position).

Note: The Post-Doc will have the opportunity to spend a few months at the University of Wisconsin-Madison, USA (cf. co-supervision with Cécile Ané)

Other information related to the position: The aim of the Centre de Biologie pour la Gestion des Populations is to understand the mechanisms that govern the evolution of populations of organisms that are important for agronomy, forestry, human health or the conservation of biodiversity.

Montpellier is a major hotspot for evolutionary and environmental research worldwide and has a vibrant research community with several hundred researchers in this domain, and highly praised graduate programs. The University of Montpellier is top ranked in the Shanghai ranking in Ecology. Montpellier lies near the Mediterranean region in the South of France and enjoys pleasant weather, fantastic nature and great cultural and city life. For information on the cost of living in Montpellier, France, you can consult the following websites:

  • Numbeo: This is probably the most comprehensive site for cost of living comparisons between cities. It offers details of the cost of food, housing, transport, etc., based on user contributions.
  • Expatistan: Another useful site that provides an overview of the cost of living in different cities, including Montpellier. It is also based on user contributions. (expatistan.com)
Type de poste

Postdoctorant.e, 18 mois.

Application and contact:

A PhD in statistics / population genetics or relevant field is expected. Informal enquiries are highly encouraged.

Please contact Arnaud Estoup (arnaud.estoup@inrae.fr). Formal application includes a letter of application with details on the motivation, a full CV, the names and contact details of two references, and the date of availability.

Candidature spontannée

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