Soil Spectroscopy and Chemometrics Co-op

• Intern

At Syngenta Crop Protection,we'repioneering solutions that safeguard global food security while championing sustainable agriculture. As a world market leader headquartered in Switzerland, we empower farmers with innovative crop protection technologies that defend against nature's toughest challenges. We unite advanced science with digital solutions to develop intelligent crop protection that maximizes yields while minimizing environmental impact. Join our mission of revolutionizing plant protection fromseedto harvest.

At Syngenta, our goal is to build the most collaborative and trustworthy team in agriculture, providing top-quality seeds and innovative crop protection solutions that improve farmers' success. We invite you to help shape the future of agriculture and play a role in safely feeding the world while caring for our planet.

Syngenta's Seeds Research Portfolio and Project Management Team is seeking a Soil Spectroscopy and Chemometrics Co-op in Des Moines, IA. This internship role will work with our soil scientists and data scientists on projects that leverage Fourier-transform infrared (FTIR) spectroscopy and advanced chemo metric and machine learning methods to rapidly characterize soil properties at scale.

As a co-op, you will work at the intersection of soil science, spectroscopy, and data science, developing and validating calibration models, exploring novel modeling approaches, and helping establish workflows that connect spectral data to actionable agronomic insights.

As part of Syngenta's Emerging Talent Program, you will gain hands‑on experience, exposure to day‑to‑day business operations, and opportunities to apply your academic knowledge to real‑world challenges while developing your professional skills.

Duration: May 2027 – August 2027

Accountabilities:

• Build, evaluate, and refine calibration models that predict soil physical and chemical properties (e.g., organic carbon, texture, pH, CEC, nutrients) from infrared spectra.
• Apply spectral preprocessing techniques (e.g., Savitzky-Golay derivatives, scatter correction, baseline correction) and evaluate their impact on model performance.
• Work with large soil spectral libraries, comprising instrument standardization and calibration transfer challenges.
• Develop and compare chemo metric (PLSR) and machine learning (Random Forest, CNN, etc.) approaches for soil property prediction.
• Collaborate closely with a multidisciplinary team of soil scientists, agronomists, and data scientists.
• Communicate methods and results clearly to both technical and non-technical stakeholders.
• The intern will operate in accordance with Syngenta Health, Safety, & Environmental (HSE) standards.

• Student must be currently pursuing a Ph.D. in Soil Science, Environmental Science, Chemometrics, Data Science, Agricultural Engineering, Analytical Chemistry, or a related field. Advanced Ph.D. students with existing spectroscopy or chemometrics research experience are strongly preferred.
• Must be a current student continuing their education upon completion of the co-op term (May 2027 through August 2027).
• All applicants must be eligible to work in the U.S.
• Demonstrated experience with vibrational spectroscopy data (MIR, NIR, and/or Vis-NIR), such as spectral preprocessing and multivariate calibration.
• Proficiency in one or more programming languages used in chemometrics and data science (R, Python).
• Experience accessing and working with soil spectral libraries (e.g., USDA KSSL, OSSL).
• Experience with chemo metric methods (particularly Partial Least Squares Regression) and familiarity with machine learning approaches for spectral data (e.g., Random Forest, CNNs, transformer-based models).
• Understanding of soil science fundamentals,…