Monsanto is seeking a highly motivated and talented genomics scientist who will perform and guide analyses using biostatistical methods, including population genetics, quantitative genetics, and bioinformatics, to support global discovery genetics research across multiple vegetable crops. The role will be positioned within the discovery genetics team and located at our R&D site in Woodland, California, USA. The scientist will manage, analyze and interpret phenotypic data and large scale genomic data, as well as develop new scripts and tools to enable routine and non-routine analyses. The candidate should be capable of effectively communicating results and providing statistical training and consulting to interdisciplinary teams.
- Leverage world-class genomic datasets to perform statistical genetic analyses and develop scripts that will support Monsanto's vegetable trait discovery pipeline.
- Implement statistical methods to identify associations between trait phenotypes and genetic markers in structured and unstructured populations (e.g. linear regression, ANOVA, mixed effects models, QTL mapping, genome-wide association mapping, genomic selection).
- Combine phenotypic and genotypic data to assess diversity and structure in vegetable germplasm.
- Generate and update consensus genetic linkage maps for various types of mapping populations. Construct reference maps that successfully integrate both genetic and bioinformatics data.
- Conduct analyses to support evaluation and improvement of genotyping platforms.
- Communicate results concisely and accurately in written and oral form to stakeholders.
- Provide statistical training and consulting with scientists and research associates.
- Direct research associates to meet business goals and identify development opportunities.
- Pursue intellectual property opportunities around project responsibilities, in collaboration with patent science and legal functions.
- Master's degree or higher in population genetics, statistical genetics, biostatistics, computational biology, bioinformatics, breeding or related field of study.
- Broad and extensive knowledge of theoretical and applied statistics, with strong skills in statistical modeling, data quality control and data mining.
- Experience constructing genetic linkage maps.
- Proficiency with one or more common statistical analysis software environments (e.g. R, SAS).
- Experience with at least one scripting language commonly used in genomics research (e.g. Python, Perl)
- Self-motivation and strong initiative.
- Ability to balance workloads from multiple competing tasks, excellent organization and time management skills.
- Outstanding written and verbal communication skills.
- PhD degree in population genetics, statistical genetics, biostatistics, computational biology, bioinformatics, breeding or related field of study.
- Applied knowledge of plant breeding
- Proficiency querying enterprise level databases
A little about us:
At Monsanto, we believe that diverse perspectives solve big challenges and deliver a broad range of solutions to help nourish our growing world.