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PhD student in statistics and bioinformatics: methodological and software developments for single-cell RNA sequencing data analysis.

This offer is available in the following languages:
Français - Anglais

Date Limite Candidature : vendredi 21 mai 2021

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General information

Reference : UMR5219-TAMAZA-008
Workplace : TOULOUSE
Date of publication : Friday, April 30, 2021
Scientific Responsible name : Neuvial Pierre
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 October 2021
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly

Description of the thesis topic

Single-cell RNA sequencing (scRNA-seq) technologies quantify the expression of thousands of genes in each cell of a biological sample. Theoretically, this makes it possible to identify and characterize the different cell types at play. The statistical analysis of scRNA-seq data generally involves (i) an unsupervized classification of the cells into cell types, followed by (ii) a differential analysis to identify marker genes for each cell type. This “classification + test” strategy induces a selection bias (or double-dipping issue), because steps (i) and (ii) are conducted on the same data [1]. This gives rise to an increased risk of errors (false positives) and non-reproducible results. The PoCI-sc project aims at developing and applying methods in order to address this statistical issue. It is an interdisciplinary project in collaboration between Institut de Mathématiques de Toulouse (IMT) and three partner labs that work with scRNA-seq data in their research: Restore (spécializing in tissue regeneration), Laboratoire Interactions Plantes-Microorganismes-Environnement (LIPME), and l'unité Génétique Physiologie et Systèmes d'Elevage (GenPhySE) at INRAE.
In this context, the person hired will mainly work on the performance evaluation of methods and their dissemination toward the community of biologists. They will first develop and implement a strategy to assess the performance of existing methods (in particular, quantification of the selection bias) based on simulations and on real data with associated ground truth. Then, they will contribute to methodological developments and implement the associated algorithms and dedicated visualization tools.
The person hired will also interact with the bioinformaticians and biologists of the partner labs, all of which are located in the Toulouse area. They will be offered the opportunity to present their works at national and international conferences of the domain, including (SMPGD: https://smpgd.fr/ and JOBIM: https://jobim2021.sciencesconf.org/).
[1] Lähnemann, D., Köster, J., Szczurek, E., McCarthy, D. J., Hicks, S. C., Robinson, M. D., … & Schönhuth, A. (2020). Eleven grand challenges in single-cell data science. Genome biology, 21(1), 1-35.

Work Context

The PhD student will join the Statistics and Optimization team of IMT (CNRS UMR 5219). The team gathers researchers, professors, research ingeneers, post-docs, and PhD students. A few of these members are specialists of methodogical developments in statistics for high-dimensional biological data. The PhD student will also be associated to the Mathematics, Biology and Health group and participate to the seminars of this group and the team.
The PhD student will be associated to the graduate school Mathématiques, Informatiques et Télécommunications de Toulouse (EDMITT).

Additional Information

The candidat must hold a MSc in applied mathematics and/or computer science. The position requires a deep knowledge in programming with R and/or python and C++. Past experience in the developmeng of visualization interfaces will be appreciated.
Excellent oral and written communication skills (in both French and English) will be required for interacting with the supervisors and collaborators, and for presenting results at conferences and writing scientific papers. We are looking for a candidate with a strong analytical mind, able to gain autonomy throughout the project, and motivated by team work in an interdisciplinar project at the interface between statistics, bioinformatics and biology.
Application should include:
• detailed CV
• at least two references (with contact information)
• one-page motivation letter
• one-page summary of the master's thesis
• masters' grades
Applications must be made through Portail Emploi du CNRS. The deadline for application is 20/05/2021.

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