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Postdoctoral Scientist in Fungicide Resistance Research - Disease Control (all genders)
The postdoc position holder will work on the most destructive disease threatening potato production: Phytophthora infestans. Due to emergence and rapid spread of sub-populations characterized by EuroBlight carrying multiple resistances to both Oomyceticides and native traits bred into potatoes in recent years, more scientific insights are needed to create awareness and advocacy on need for implementation of sustainable fungicide resistance management strategies.
YOUR SPECIFIC RESPONSIBILITIES
1. Join highly motivated lab-team to monitor European P. infestans populations by use of next generation sequencing methods to detect known and new nucleotide polymorphisms and characterize their phenotypes
2. Identify relevant stress factors defining evolutionary potential by characterizing selected mutants/EuroBlight-types with regard to pleiotropic effects, e.g. on virulence or competitive fitness
3. Generation of in-vivo experimental data on the effect of Oomyceticides in plant-pathogen systems
4. Use Next Generation Sequencing and data science to get nucleotide diversity data to better understand relationships between P. infestans sub-populations and fungicide resistance evolution
5. Implement efficient gene editing protocols in genetic backgrounds of P. infestans, including proof-of-concept and optimization experiments
6. Possibly extend experience generated on P. infestans to other important plant pathogens like Plasmopara viticola
7. Pro-actively generate project-related ideas for experimental plans and equipment needed by literature review and interaction with internal and external scientists
8. Independent documentation, evaluation, presentation of experimental methods and data to project members and beyond, including contribution to scientific conferences
9. Publication of results in peer-reviewed journals
WHO YOU ARE
10. PhD (all genders) in the area of molecular biology, genetics, plant pathology or related discipline
11. Strong background in molecular biology in true fungi or oomycetes
12. Hands on experience in plant pathology, DNA extraction, quantification and next generation sequencing technologies
13. Profound knowledge in plant pathology, experimental design, data science and/or agriculture
14. Knowledge in cloning, DNA variant screening, fungal transformation or gene editing and subsequent genetic data analysis is beneficial
15. You are self-motivated with a results-oriented mindset, eager for hands-on experimentation and driven by scientific curiosity, with excellent organizational skills
16. Strong verbal and written communication skills, looking forward to working in an interdisciplinary and cross-functional team of scientific and technical experts
17. Excellent proficiency in English, both written and spoken; German knowledge is beneficial
WHY BAYER?
What counts for you, also counts for us! We believe in individual definitions of career, success, and work-life balance. You can expect a working environment in which you are welcomed, supported, and encouraged to bring your whole self to work. In addition to your work in dynamic and diverse teams, you can expect numerous benefits during your internship, such as:
18. A job ticket that allows you to flexibly and sustainably design your commute to work
19. The Corporate Benefits program, which entitles you as a Bayer employee to discounts from more than 150 brands
20. Professional development learning opportunities such as LinkedIn Learning and Education First
Ever feel burnt out by bureaucracy? Us too. That’s why we’re changing the way we work— for higher productivity, faster innovation, and better results. We call it Dynamic Shared Ownership (DSO). Learn more about what DSO will mean for you in your new role here:
This is a 2-year contract starting as early as possible. Please upload your online application including cover letter, CV and relevant certificates in one summarised file. We are looking forward to meeting you!
#LI-DE
DEINE BEWERBUNG
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Standort: Monheim
Division: Crop Science
Referenzcode: 819687