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Texas A&M University System

Texas public university system

Assistant Professor - AI in Agriculture

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeTemple, TX, USANo salary listed

About the Job

Requirements

  • A Ph.D. in AI, Data Science, Agricultural and Biological Engineering, Natural Resources, Soil and Crop Sciences, Agronomy, Computer Science, or a closely related field by the hire date. Candidates with a closely related degree must demonstrate a strong academic background or a research program explicitly focused on AI applications in agriculture.
  • A strong background in artificial intelligence, machine learning, and data analytics as applied to agricultural and environmental systems.
  • Proficiency in programming languages such as Python, R, Java, or C++, and machine learning frameworks or libraries such as Pandas, NumPy, TensorFlow, or PyTorch.
  • Evidence of, or the ability to produce, peer-reviewed publications of original research.
  • Potential to develop research proposals and sustain a funded, high-impact research program.
  • Excellence in verbal and written communication.
  • Team-building skills, collaboration capacity, and project management abilities.
  • Ability to multitask and establish effective working relationships.
  • Knowledge and understanding of the mission and role of the Land Grant University System.

Responsibilities

  • Establish and lead a nationally recognized, externally funded, and self-sustaining research program focused on the sustainability, health, productivity, and marketability of agriculture, natural resources, and environmental systems.
  • Conduct interdisciplinary research in artificial intelligence applications within agriculture and natural resources, addressing challenges in artificial intelligence and robotics in intelligent farming systems, smart agriculture and Internet of Things integration, precision and autonomous agriculture, crop and livestock systems management, sustainable production systems, and large-scale collaborative research.
  • Secure competitive funding from external sources.
  • Supervise and mentor postdoctoral associates or research scientists.
  • Supervise student research projects, serve on graduate committees, and mentor students in scholarly activities.
  • Collaborate with faculty, industry partners, and community service providers to ensure research relevance and applicability to stakeholders.
  • Publish research results in peer-reviewed journals and technical reports.
  • Share models and tools with relevant stakeholders, land managers, and the broader scientific community.
  • Build institutional capacity in artificial intelligence research and emerging technologies across the institution and the College of Agriculture and Life Sciences to enhance research and outreach.
  • Direct the work of support staff, other technical personnel, and graduate students assigned to the project.

Desired Qualifications

  • Experience developing and applying innovative, data-driven approaches that integrate artificial intelligence with geospatial analysis, remote sensing, robotics, and related digital technologies applied to agriculture, environmental science and technology, natural resource management, or plant science and biology.
  • Prior academic, postdoctoral, or professional experience.
  • Experience working collaboratively in interdisciplinary teams and engaging with agricultural and environmental stakeholders.
  • Grant writing experience and evidence of obtaining external funding through competitive grant programs.

About the Company

Texas A&M University System

Texas public university system

Texas A&M University System is a statewide public university system combining higher education, research, and public-service agencies. The system coordinates universities and state agencies that deliver teaching, research, extension, engineering, health, and community programs. It serves students, faculty, researchers, public agencies, industries, and communities throughout Texas. Its operating model centers on autonomous member institutions connected through system governance, shared services, public funding, and statewide missions. Teams work across instruction, research, healthcare, extension, engineering, technology, administration, facilities, and public service. Teams support coordinated daily delivery.

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