KeyGene is the go-to AgBiotech company for higher crop yield & quality. With our intellectual capital, solution driven approach and collaborative spirit, we work for the future of global agriculture with partners in the AgriFood sector. Using our proprietary technologies and non-GM approaches, we support customers with the development of new and improved crops.
Our goal is to help organizations with their toughest R&D challenges, combining our cutting edge breeding technologies, bioinformatics & data science expertise and plant-based trait platforms. At KeyGene, we work in an international environment with more than 140 professionals from all over the world. Our company is based in Wageningen, Netherlands and Rockville, MD, USA
KeyGene’s innovation platform for Genomic Breeding comprises technologies for complex trait analysis, digital phenotyping, and the computational design of breeding strategies. Over the past years, we have built innovative methods, using deep learning and artificial intelligence to design and evaluate optimal breeding strategies from phenotypic, molecular marker and whole-genome data. These technologies respond to the demand of our customers to transform their breeding practices and to accelerate crop innovation.
As a Quantitative Geneticist you will strengthen our team of Computational Breeding Solutions, which is part of the Bioinformatics & Modeling Department. With your background in statistical methods used in traditional and genomic evaluation and in genome-wide association analysis, you will contribute to the application of these technologies in the commercial improvement of crops and traits. You will also provide expert advice in population design and field trial implementation for genomic evaluations. A very important part of the position involves working with a team of geneticists, mathematicians and software developers on the development of a highly innovative breeding simulation and decision support platform.
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10 - 15 years
2 - 5 years
> 15 years
|Job Location:||Wageningen, Netherlands|
|Keywords:||Data, scientist, genetics, quantitative, R, C++, Python, GWAS, Genomic Selection, PhD|