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Field of Work: Research & Development
Location:
Einbeck, Lower Saxony, DE
Legal Entity: KWS SAAT SE & Co. KGaA
Contract Type: Regular
Is Full Time?: Yes
Onsite/ Remote:
Job ID: 16250
The Breeding Technology Team for Maize & Oilseed Crops is seeking a passionate and forward‐thinking Advanced Scientist in Quantitative Genetics and Biostatistics (m/f/d) for Trait Discovery to join us on a full‐time, permanent basis.
In this key role, you will help drive innovation in trait discovery and genetic analysis for some of the world’s most important crops. Working closely with breeders, biostatisticians, trait genetics specialists, marker development teams, and molecular genomics experts, you will develop novel analytical concepts and prototype advanced statistical approaches that support data‐driven breeding decisions.
Based at the KWS headquarters in Einbeck (Lower Saxony, Germany), you will contribute to cutting‐edge work in genome analytics, trait mapping, and quantitative genetics, supporting breeding programs in maize, sunflower, and oilseed rape and helping accelerate gene discovery and innovation across KWS.
KWS is one of the world’s leading plant breeding companies. Nearly 5,000 employees in more than 70 countries generated net sales of around €1.68 billion in the fiscal year 2023/2024. A company with a tradition of family ownership, KWS has operated independently for almost 170 years. It focuses on plant breeding and the production and sale of seed for sugarbeet, corn, cereals, vegetables, oilseed rape and sunflower. KWS uses leading-edge plant breeding methods to continuously improve yield for farmers and plants’ resistance to diseases, pests and abiotic stress. To that end, the company invested more than €300 million last fiscal year in research and development. For more information: www.kws.com/career . Follow us on LinkedIn® at https://linkedin.com/company/kwsgroup/ .
Our data privacy policy for candidates is available on www.kws.com/dataprotection . Please select the country where the job you applied for is posted in and, if applicable, the specific business unit.
Job Segment: R&D, Research Scientist, Statistics, Data Mining, Research, Science, Data, Technology
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