Tenure-TrackTenured Assistant or Associate Professor, AI for Autonomous Agricultural Systems-Robotics & Sensing

Position Description: The Department of Biological and Agricultural Engineering in the College of Agriculture and Life Sciences at Texas A&M University invites applications for a 9-month full time position in Artificial IntelIigence (AI) for Autonomous Agricultural Systems- Robotics & Sensing. Applicants will be considered for the titles of Assistant Professor (Tenure-Track) and Associate Professor (Tenured). The department has top-ranked graduate and undergraduate programs and a strong research emphasis in machinery systems and postharvest process engineering. This position is part of a four-position cluster hire in AI in Agriculture across the College of Agriculture and Life Sciences to build research capacity in this area.

Within this cluster the Biological and Agricultural Engineering position focuses on AI-enabled autonomy robotics and precision operations in agricultural production. This position should address major challenges facing agriculture such as efficiency labor costs and availability emerging biotic threats water use and efficiency and soil health. This position requires strong technical expertise in AI sensing automation and controls or robotics as well as knowledge of agricultural systems.

Duties and Responsibilities: The successful candidate will develop an internationally recognized integrated research and teaching program that advances intelligent agricultural machinery systems and prepares students for careers at the intersection of agriculture and technology. Potential research areas may include but are not limited to agricultural autonomy collaborative robotics AI-enabled sensing systems cyber-physical systems for agriculture federated learning edge computing development of novel AI algorithms for agricultural applications embodied AI simulation to reality transfer and systems engineering incorporating big data and artificial intelligence.

Agriculture will be transformed in the coming decades by the adoption of robotics and data-driven systems. This position will lead innovation in development and in-field evaluation of these agricultural systems to increase farmer profitability minimize resource use and enhance the resilience of agriculture in Texas and beyond. While the candidate should have strong engineering expertise transdisciplinary collaboration will be necessary for success in this role. Multiple resources are available through the college and university to support collaborative efforts. These include but are not limited to the Texas A&M Institute of Data Science and the High Performance Research Computing Center which recently brought online the most powerful university supercomputer in the US. AgriLife has invested in data-driven agriculture initiatives such as the Automated Precision Phenotyping Greenhouse and the AgriTech Innovation Farm Hub. Furthermore AgriLife has 13 research and extension centers across Texas and maintains strong connections with commodity groups and farmer organizations.

The successful applicant will develop and teach courses in the Department of Biological and Agricultural Engineering. The individual will develop courses in agricultural autonomy/robotics for undergraduate and graduate students in Biological and Agricultural Engineering and Agricultural Systems Management. An undergraduate minor in AI-Enabled Agricultural Systems will be established with courses developed from this cluster hire.

The individual will advise and mentor undergraduate and graduate students and other research personnel. The successful candidate will attract extramural funding and publish research in appropriate peer-reviewed journals. They will participate in service activities both internally and professionally to complement their teaching and research programs.

Required Qualifications: Applicants must possess a Ph.D. in Biological and Agricultural Engineering or a closely related engineering discipline. Candidates who have completed all Ph.D. requirements except the dissertation (ABD) will be considered provided they demonstrate clear progress toward completion. Candidates must have demonstrated experience or potential to build strong research and teaching programs. Successful candidates are expected to have effective verbal and written skills an ability to work both independently and in multi-disciplinary teams and a willingness to advise and mentor students.

Desired Qualifications: Applicants should be licensed or qualified to obtain a license as a Professional Engineer. Experience deploying automated systems in agricultural environments is highly desirable.