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, Tenure Track Faculty Position Sustainable Food and Agricultural Systems beginning August 1, 2026. The position is posted as 45% Research, 45% Teaching and 10% Service. Applicants will be considered for the faculty title of Assistant Professor.

The successful candidate will establish an integrated teaching and research program of international recognition focused on one or more of (but not limited to) the following areas: reliable, robust, sustainable food and agricultural supply chains to address food security, and food/energy/water waste and loss; applications of data analytics and big data tools for food security and smart agricultural systems engineering for food, energy, environment and health systems.

The candidate will leverage cutting-edge, data-driven approaches and technologies, including applications of artificial intelligence (AI) to agricultural systems sustainability. Teaching responsibilities will include undergraduate courses in biological and agricultural engineering and agricultural systems management on subject matter appropriate to the individual's expertise. In addition, the incumbent will advise both undergraduate and graduate students. Participation in professional development activities and an appropriate level of service to the department, institution, and/or profession is expected.

Requirements

Applicants must possess a Ph.D. in Biological and Agricultural Engineering or a closely related field. Candidates who have completed all Ph.D. requirements except the dissertation (ABD) will be considered provided they demonstrate clear progress toward completion. Preference will be given to candidates with demonstrated experience or potential for developing research and teaching programs with expertise in one or more of the following areas of research: production and supply chain, water-energy-food nexus, LCA and circularity, big-data analysis, machine learning, deep learning, AI tools, smart agriculture and circular bioeconomies.

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.

Applicants must be licensed or be eligible to obtain a license as a Professional Engineer at the time of appointment.