Breeding Simulation and Optimization Intern

Driscoll’sWatsonville, CA
8d$19 - $40Hybrid

About The Position

This internship offers students in operations research, industrial engineering, computer science, data science, plant breeding, quantitative genetics, or related disciplines a unique opportunity to work within a highly collaborative agricultural R&D team focused on berry breeding. The intern will work closely with Driscoll’s global breeding teams and breeding analytics scientists, gaining exposure to researchers across field, lab, and leadership roles. The primary responsibilities include simulating berry breeding programs using software such as AlphaSimR, breedSimulatR, PyBrOpS, or comparable tools. These simulations will be based on defined breeding scheme parameters to evaluate long term genetic gain across different breeding scenarios. The intern will then develop optimization strategies—either by leveraging existing tools or designing new algorithms—to recommend improved breeding program designs. As part of building this modeling and optimization framework, the intern will assist in data collection, utilize historical datasets, and perform analytical tasks that support future program development. Additionally, they will have opportunities to participate in hands on breeding activities during peak season, including seedling selection, fruit evaluation, and phenotyping, with the amount of fieldwork tailored to their interests. At the conclusion of the internship, the intern will prepare a written report summarizing their findings and will deliver an oral presentation outlining the results of their primary projects.

Requirements

  • Currently enrolled in a bachelor’s or Graduate program in Operation Research, Industrial Engineering, Computer Science, Data Science, Plant Breeding, Quantitative Genetics
  • Strong R, Python or other programming languages
  • Driver’s license, transportation, and the ability to be covered under a company-sponsored vehicle insurance program.
  • Ability to build components of an overall workflow
  • Understand the scientific method
  • Be attentive to details
  • Be able to work in office, lab, and outdoor field environments (lab and outdoor components)
  • Option to work remotely part of the week.
  • Have great communication skills.
  • Be reliable, honest, and trustworthy.

Nice To Haves

  • Coursework in biology, plant sciences, plant breeding, or genetics related subjects is considered a plus
  • Experience in breeding program simulation/optimization and/or operation research is preferred

Responsibilities

  • Work with the breeding teams to understand the foundations and methodologies of berry breeding
  • Gain understanding of parameters needed for running simulation for berry breeding programs
  • Develop simulation framework to monitor long-term genetic gain
  • Develop optimization strategies/algorithm to various simulated scenarios
  • Share findings through detailed documentation and summarized reports
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