Postdoc in Quantitative Genetics: We are seeking a highly motivated Postdoc in Quantitative Genetics to join the INCREASE project at the GQE Le Moulon laboratory in Gif-sur-Yvette, France. The project aims to utilize molecular information and advanced statistical modeling techniques to identify genetic loci associated with complex traits variation in common bean crops. The hired person will focus on studying the relationship between genes and traits, improving breeding methods, and understanding how genetics plays a role in adapting to different environments.
Designation: Postdoc
Research Area: Quantitative Genetics
Location: UMR GQE Le Moulon, Gif-sur-Yvette, France
Eligibility/Qualification:
- Bac+8 / Doctorate degree in quantitative genetics, statistics/biostatistics, or computational biology applied to quantitative genetics.
- Experience in GWAS analysis and statistical modeling.
- Proficiency in R programming, large dataset management, and data visualization.
- Prior knowledge of common bean and/or climate variables is a plus.
Job Description: The recruited Postdoc will be involved in the following activities:
- Conducting genome-wide association studies on various traits of interest related to bean development in different environments.
- Evaluating the impact of GxE interactions on the expression of target traits and performing meta-analysis of GWAS to identify loci involved in GxE interactions.
- Identifying genomic regions associated with specific environmental factors and evaluating their contributions to phenotypic variation, aiding in understanding local adaptation.
- Investigating the potential overlap between GxE interaction loci and environmental association loci to understand the genetic mediation of response to specific environmental cues.
- Developing genomic prediction models for bean development and growth traits, exploring the inclusion of GWAS-identified loci.
- Utilizing genomic selection prediction to assess the performances of the R-core panel and identify original sources of diversity.
Expected Outcomes:
- Identification of genomic regions associated with agronomic traits in bean crops, providing valuable insights for marker-assisted selection and breeding programs.
- Characterization of GxE interactions to develop environment-specific cultivars and optimize production strategies.
- Identification of genetic variants responsible for adaptation to specific environmental conditions, aiding in the development of stress-tolerant bean varieties.
- Advancing the understanding of the complex interplay between genetics and environment in shaping phenotypic variation in beans.
- Identification of lines from the R-core panel for future phenotyping and use as sources of diversity.
Working Environment, Starting Date: This post-doctoral position is funded by the European INCREASE project. The candidate will work at GQE Le Moulon lab and be supervised by Elodie Marchadier (Biology Professor) and Tristan Mary-Huard (Statistics Researcher).The position will involve close collaboration with Laurence Moreau (Senior Researcher in Quantitative Genetics) and Christine Dillmann (Professor in Evolutionary Biology). The starting date is anticipated to be September 1, 2023, and the position will last for 18 months (with a possible extension of up to 6 months).
How to Apply: To apply for this position, please send the following documents to the specified contact:
- Cover letter expressing your interest and suitability for the position
- Curriculum vitae (CV)
- Any additional supporting documents
For further inquiries or to submit your application, please contact [contact person] at [contact email].
Last Date for Apply: [Last Date for Apply] (Applications will be accepted until this date)
Table: Position Details
| Position | Postdoc in Quantitative Genetics |
|---|---|
| Contract type | CDD |
| Duration | 18 months (renewable) |
| Education Requirement | Bac+8 / Doctorate, Grandes Écoles |
| Research Area | Quantitative Genetics |
| Location | UMR GQE Le Moulon, Gif-sur-Yvette (France) |
| Starting Date | 1 September 2023 |
Table: Required Skills
| Skills |
|---|
| PhD in quantitative genetics or related field |
| Experience in GWAS analysis |
| Proficiency in R programming and statistical modeling |
| Knowledge of large dataset management |
| Prior knowledge of common bean and/or climate variables (desirable) |
