The Department of Soil and Crop Sciences, College of Agriculture and Life Sciences at Texas A&M invites applications for one full-time, tenured or tenure-track open rank position (Assistant, Associate, or Full professor). This 9-month academic appointment will begin on or after August 1, 2024 with research (60%), teaching (30%), outreach, and service (10%) responsibilities.

The successful applicant will be responsible for developing a strong research program integrating data science approaches (advanced statistical techniques, machine learning, deep learning, AI or similar), data management approaches (curation and publication of reference data sets), latest sensor technology, and/ or advanced modeling techniques for applications in agricultural sciences. Emphases will be on the applications of machine learning and artificial intelligence techniques for solution-driven applications in genomics, phenomics, high-throughput above-ground and below-ground phenotyping, agronomy, soil science, climate-smart agriculture, microbiome dynamics, or similar.

The applicant will work closely with genomics and genetics researchers, plant breeders, crop physiologists, agronomists, and soil scientists within AgriLife Research and AgriLife Extension faculty both on and off-campus. Integration with the Texas A&M Institute of Data Science is expected, along with scientific collaborations in the region, nationally, and internationally to establish a highly impactful, extramurally funded research program. The successful individual will develop and teach a course on applied data science in agriculture and deliver an additional undergraduate or graduate course in consultation with the department. The individual will be expected to publish regularly in peer-reviewed journals appropriate to the discipline.

A Ph.D. or equivalent doctoral degree in environmental science, plant or crop science, computer science, bioinformatics, statistics, remote sensing, agriculture, biosystems engineering, electrical engineering, or related disciplines is required. Strong knowledge and experience in data science and agricultural data are both required. Experience working with crops, handling large datasets, and writing grants is desired.

To be given full consideration, please submit applications by May 1, 2024.