Assistant Professor - AI for Smart Agriculture

Texas A&M University System; Temple (TX); On-site; USD 80,000 - 120,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life insurance

Long-term disability insurance

Paid holidays

Sick leave

Vacation

Job summary

Texas A&M AgriLife Research in Temple, TX seeks an Assistant Professor of AI in Agriculture to develop a nationally recognized, externally funded research program in AI applications for agriculture and natural resources. The 12‑month, non‑tenure‑track position will be based at the Blackland Research and Extension Center with academic affiliation in a relevant Texas A&M department.

The successful candidate will employ machine learning, data science, remote sensing, robotics, and other digital

Qualifications

• Ph.D. in AI, Data Science, or closely related field by hire date.
• Strong background in AI, ML, and data analytics for agricultural/environmental systems.
• Proficiency in programming languages and ML frameworks.
• Evidence of peer‑reviewed publications; ability to develop funded, high‑impact research.
• Grant writing experience is a plus.

Responsibilities

• Establish and lead an externally funded, nationally recognized research program.
• Conduct interdisciplinary AI research in agriculture and natural resources.
• Secure competitive external funding.
• Supervise postdocs, researchers, and graduate students.
• Collaborate with faculty, industry partners, and stakeholders to ensure relevance.

Skills

AI & ML in agriculture

Data analytics

Programming languages (Python, R, Java

C++

ML frameworks (TensorFlow, PyTorch)

Education

Ph.D. in AI or related field

Tools

Python

R

Java

C++

TensorFlow

PyTorch

Job description

Texas A&M AgriLife Research in Temple, TX seeks an Assistant Professor of AI in Agriculture to develop a nationally recognized, externally funded research program in AI applications for agriculture and natural resources. The 12‑month, non‑tenure‑track position will be based at the Blackland Research and Extension Center with academic affiliation in a relevant Texas A&M department.

The successful candidate will employ machine learning, data science, remote sensing, robotics, and other digital