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Apply online at: http://www.monsanto.com/careers/pages/jobsearch.aspx
Search on Requisition Number 00VSX
Analytics Automation Intern
Monsanto Company
Monsanto is passionate about using science and technology to improve agriculture. Monsanto scientists are engaged in Research and Development (R&D) to revolutionize plant breeding and biotechnology. Our Trait & Field Solutions (TFS) organization plays a key role in delivering the world's largest and most commercially successful crop biotech trait portfolio through excellence in field operations, advancement of genes and development of commercial trait conversions. This position offers the opportunity to work with state-of-the-art experimental techniques and analytical platforms along side a team of mathematicians and statisticians who work collaboratively with researchers and other statisticians across our R&D organization.
The Analytics Automation intern will work closely with members of TFS Global Analytics, Information Technology (IT) R&D, and TFS Product Assessment scientists for development of statistical analysis modules in R with computationally efficient algorithms. This will involve mathematical and statistical algorithms for fitting complex models with real-world impact applied to field experiments.
Required Skills/Experience:
- Candidates must be currently enrolled in a Master's or PhD degree program in Computational Statistics, Computational Mathematics, Computer Science, or Computational Biology.Graduate students in Statistics, Mathematics, Biostatistics, or Bioinformatics with strong background in development of efficient computer algorithms are also eligible.
- Expertise in numerical methods for dealing with large and high dimensional unbalanced data with missing values
- Proficiency in R programming with strong experience in development and usage of R packages with computational efficiency
- Basic knowledge of Design of Experiments, Analysis of Variance, Mixed Model, Regression, and other statistical tools and implementation of these techniques in R
- Plans to graduate no earlier than December 2015.
- Cumulative GPA of at least 3.0/4.0.
- Details and results-orientated with ability to work independently
- Strong communication and problem solving skills
- Personal transportation
Desired Skills/Experience:
- Experience with numerical linear algebra for solving linear systems with sparse and ill-conditioned matrices is highly desirable.
- Background and training in crop science.
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Radha Mohanty
Monsanto
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