Post-doctoral position in Gene editing and agroecology
Breeding for more resilient and resource saving plant species rendering multiple services is a major lever for future agricultural systems which will be multi-performant, competitive and yet sustainable under conditions of climate changes.
The project will deal with genetic improvement of camelina by gene editing to better contribute to the agroecological transition. Camelina [Camelina sativa (L.) Krantz] is an allohexaploid oilseed crop in the family Brassicaceae, which attracts increasing interest as a model crop for translational research. From an agronomic perspective, Camelina's short life cycle opens interesting possibilities for double cropping. These strategies could be greatly facilitated if the life cycle could be further shortened to flexible integration of camelina in double-cropping strategies in Europe. Producing camelina lines that will be more favorable to double-cropping systems will have positive agro-ecological benefits: decreasing the duration of land being left bare will reduce soil erosion; integration of camelina in European rotation schemes will increase crop diversity. Decades of research have identified several key genes that negatively regulate the transition to flowering in arabidopsis. Multiplex editing in camelina succeeded in obtaining early flowering lines.
The objective of the project will be to further characterized the different edited lines in particular for its metabolic profile of its seeds and oil and to develop a pipeline enabling detection of rare edited alleles among wild type population to estimate gene fluxes.
should include a cover letter and a detailed CV including two scientific references that must be sent to Contact
Applications will be accepted until the position is filled.
Selected candidates will be invited for an interview.
Starting date: from 01/09/2022 – one year contract (possibility of extension)
Salary: 2400 - 2900 euros (according to previous professional experience) + residence allowance of 3% of gross salary
Expertise or training in molecular genetics is desired and experience in analyzing NGS data would be appreciated.