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Sugarcane Statistical Geneticist (mons-00010724) - (Campinas, Brazil)
Company: Monsanto
Website: http://www.monsanto.com
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Open Til: 20-Dec-09
Industry Sector: Agribusiness
Industry Type: Crop Protection/Chemicals
Career Type: Researcher/Scientist
Job Type: Full Time
Minimum Years Experience Required: N/A
Salary: Competitive
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Job Description:
- Large scale analyses of plant breeding data (markers, phenotypes & pedigree) to support Monsanto's sugarcane breeding effort
- Develop generalized procedures to evaluate and improve
the effectiveness of sugarcane parent & variety selection and testing programs at different stages of product development and optimize product placement strategies.
The selected candidate will be able to:
Coordinate a group of researchers to develop and test enhanced methods of predicting the performance of populations, lines, and hybrids.
Provide written and oral presentations to peer and management groups
Provide solid interpretation and recommendations based on quantitative data analysis to drive improvements to the existing breeding practices.
Required Skills:
- Ph.D. in plant breeding, genetics or statistics, or equivalent experience with expertise in the application of plant quantitative genetics methodology.
- Excellent quantitative skills including experience in the use of commercial statistical software (e.g., SAS, R, ASREML, etc.) or custom (Fortran, C++, C#, etc.) programs for the design and analysis of experiments, and experience working with large databases is required.
- Previous experience with mixed-model methods for genetic evaluation is a plus.
- Significant experience in marker-assisted selection, molecular breeding or genomic selection
- Strong understanding of plant breeding
- A solid foundation in statistical theory and with a
strong interest in applied statistical analysis
methodologies
Desired Experience/Education/Attributes:
- Background in Agronomy and/or Plant Breeding in sugarcane
- Excellent communication skills, with the ability to summarize complex concepts in language understandable by scientists from a variety of disciplines
- Fluent in, both oral and written, English.
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