Phd Position F - m Stochastic Modelling Of Dynamical Resource Allocation And Analysis Of Single-Cell Data H/F INRIA
Montbonnot-Saint-Martin - 38 CDD- 🕑 36 mois
- Bac +5
- Service public des collectivités territoriales
Les missions du poste
PhD Position F/M Stochastic modelling of dynamical resource allocation and analysis of single-cell data
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : CDD
Niveau de diplôme exigé : Bac +5 ou équivalent
Fonction : Doctorant
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 Ph.D. project will BE carried out in the project-team MICROCOSME at Inria Grenoble - Rhône-Alpes under the joint supervision of Aline Marguet (and Hidde de Jong () within the framework of the ARBOREAL ANR project (). MICROCOSME is an interdisciplinary team that includes applied mathematicians, engineers, computer scientists, biologists as well as experimentalists from themicrobiology/biophysics team BIOP of the Université Grenoble-Alpes ().
Mission confiée
Gaining an understanding of the cellular processes underlying bacterial growth is crucial for fundamental research in biology as well as for applications in biotechnology, health, and environmental technology. New experimental technologies have been developed to monitor growth and gene expression at the single-cell level, opening the path to the exploration of the origins of variability in growth phenotypes within a population of bacterial cells. So far, the data obtained from these technological breakthroughs have been exploited only in part. In particular, appropriate mathematical models and methods to relate single-cell gene expression data with the emergence of growth variability in a population are rare [1].
The ARBOREAL ANR project aims at developing a new mathematical framework for the analysis of growth variability from single-cell data, by combining structured branching processes [2, 3] with models of bacterial growth [4] at the single-cell level. We will obtain a new class of stochastic individual-based models, called Branching Resource allocation Processes (BRP), that will enable investigation of the variability of growth phenotypes in a proliferating microbial population in terms of the variability of physiological and cell division processes. The development of the BRP framework will entail modelling, analysis, and inference, and will exploit microfluidics experiments comprising single-cell measurements of growth and expression levels of ribosomes and enzymes in the model organism Escherichia coli [5].
The proposed Ph.D. project involves the development, numerical simulation, and analysis of branching resource allocation processes and the application of this new framework to existing single-cell datasets in the team to study the onset of growth variability in bacterial populations.
Principales activités
Using a variety of mathematical tools and algorithmic approaches (Continuous-Time Markov chains, Mixed-Effects modelling, Branching processes, stochastic simulation) as well as single-cell gene expression datasets, we will address several of the following points :
- Explore different combination of models of single-cell resource allocation and cellular replication (varying lifetime distribution for the individuals, possible asymmetry in the sharing of the cell content at division, switching mechanisms etc.)
- Analyse the new BRP models (asymptotic behavior, comparison of population and lineage dynamics, compute the large population limit and compare with existing population-average resource allocation models).
- Develop numerical simulation tools for the BRP models.
- Use the BRP framework to analyse single-cell E. coli datasets from our laboratory [5] and other datasets to relate growth phenotypes on the population level to resource allocation strategies on the single-cell level.
[1] Thomas, P., G. Terradot, V. Danos, and A. Y. Weie, Sources, propagation and consequences of stochasticity in cellular growth. Nat Commun 9 :4528, 2018.
[2] A. Marguet, Uniform sampling in a structured branching population, Bernoulli, 25, pp. 2649-2695, 2019.
[3] S. Méléard and V. Bansaye, Stochastic Models for Structured Populations : Scaling Limits and Long Time Behavior, Springer Cham, 2015.
[4] N. Giordano, F. Mairet, J.-L. Gouzé, J. Geiselmann, and H. de Jong, Dynamical allocation of cellular resources as an optimal control problem : Novel insights into microbial growth strategies, PLoS Comput Biol, 12, p. e1004802, 2016.
[5] A. Pavlou, E. Cinquemani, C. Pinel, N. Giordano, M. Van Melle-Gateau, I. Mihalcescu, J. Geiselmann and H. de Jong. Single-cell data reveal heterogeneity of investment in ribosomes across a bacterial population. Nat Commun16, 285 (2025).
Compétences
Interested candidates are expected to have a solid preparation in dynamical system / stochastic process modelling and analysis and some familiarity with scientific programming, and to BE interested in biological applications and data processing.
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 (90 daus per yerar) 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
L'adresse du poste
Localisez l'entreprise et calculez votre temps de trajet en un clic !
Calculer mon temps de trajet
Bienvenue chez INRIA
A propos d'Inria
Inria est l'institut national de recherche dédié aux sciences et technologies du numérique. Il emploie 2600 personnes. Ses 215 équipes-projets agiles, en général communes avec des partenaires académiques, impliquent plus de 3900 scientifiques pour relever les défis du numérique, souvent à l'interface d'autres disciplines. L'institut fait appel à de nombreux talents dans plus d'une quarantaine de métiers différents. 900 personnels d'appui à la recherche et à l'innovation contribuent à faire émerger et grandir des projets scientifiques ou entrepreneuriaux qui impactent le monde. Inria travaille avec de nombreuses entreprises et a accompagné la création de plus de 200 start-up. L'institut s'eorce ainsi de répondre aux enjeux de la transformation numérique de la science, de la société et de l'économie.
Hellowork a estimé le salaire pour ce métier à Montbonnot-Saint-Martin
Le recruteur n'a pas communiqué le salaire de cette offre mais Hellowork vous propose une estimation (fourchette variable selon l'expérience).
Estimation basée sur les données INSEE et les offres d’emploi similaires.
Estimation basse
36 600 € / an 3 050 € / mois 20,11 € / heureSalaire brut estimé
43 800 € / an 3 650 € / mois 24,07 € / heureEstimation haute
52 500 € / an 4 375 € / mois 28,85 € / heureCette information vous semble-t-elle utile ?
Merci pour votre retour !
- Montbonnot-Saint-Martin - 38
- CDD
Créez une alerte
Pour être informé rapidement des nouvelles offres, merci de préciser les critères :
Finalisez votre candidature
sur le site du recruteur
Créez votre compte pour postuler
sur le site du recruteur !
sur le site du recruteur
sur le site du recruteur !
Ces offres pourraient aussi
vous intéresser
Recherches similaires
- Job Data scientist
- Job Informatique
- Job Grenoble
- Job Voiron
- Job Bourgoin-Jallieu
- Job La Tour-du-Pin
- Job Morestel
- Job Saint-Marcellin
- Job La Mure
- Job Vienne
- Job Villard-de-Lans
- Job Salaise-sur-Sanne
- Job Développeur
- Job Technicien support informatique
- Job DevOps
- Job Développeur Java
- Job Chef de projet informatique
- Entreprises Informatique
- Entreprises Data scientist
- Entreprises Montbonnot-Saint-Martin
- Job Data
- Job Fonction publique
- Job Collectivités
- Job Fonction publique territoriale
- Job Public
- INRIA Montbonnot-Saint-Martin
- INRIA Data scientist
{{title}}
{{message}}
{{linkLabel}}