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Reference : UMR5797-JERBAU-031
Workplace : GRADIGNAN
Date of publication : Tuesday, August 20, 2019
Scientific Responsible name : Hervé Seznec
Type of Contract : PhD Student contract / Thesis offer
Contract Period : 36 months
Start date of the thesis : 1 November 2019
Proportion of work : Full time
Remuneration : 2 135,00 € gross monthly
Description of the thesis topic
Living organisms are constantly exposed in their environment to low doses of ionizing radiation (IR). Although the biological effects induced by the IRs are well known at high dose, low-dose radiation-induced effects remain an open question. Thus, the aim of this thesis is to characterize the radio-induced molecular consequences on RNA metabolism following exposure at highly controlled dose. The originality of this project is based on the combination of the use of Monte Carlo code (Geant4 toolkit), nuclear microprobe (irradiation) and high-throughput sequencing applied to C. elegans. The PhD student will contribute to the development and application of bioinformatics tools developed by the iRiBio team. The PhD student will participate in the exploitation of the data obtained by modeling the biological effects of IR, from the cell scale to the organism (C. elegans) and will make the link with the experimental activities (irradiation and sequencing) by developing the bioinformatics tools needed for transcriptome and epitranscriptome analysis.
The doctoral student will join the research group iRiBio of CENBG and ARNA of the IECB and will evolve in a context of interdisciplinary research (physics-biology-informatics). The doctoral student will participate in the implementation of the experimental procedures and analyzes and will contribute to the writing of the publications/communications of his results. The doctoral student will evolve in an L2 type laboratory. It is essential that the successful applicant has a background in microbiology, molecular biology or bioinformatics.
Constraints and risks
This is a cross-disciplinary project involving elements of radiation biology, molecular biology, statistic, informatic. Knowledge of computing codes (R, python) is recommended for bio-statistics and bioinformatics applications.
No constraints or special risks :
- Exposure to ionizing radiation: public area level
- Biology: laboratory safety level 2
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