Assistant Professor - AI for Agriculture and Natural Resources

Tenure-Track Faculty Positions in AI and Machine Learning for Agriculture and Natural Resources

The College of Agriculture and Natural Resources at the University of Maryland seeks candidates with expertise in utilizing AI and machine learning to improve decision-making in agriculture, agroecology, and/or natural resources. Applications are invited for one or more tenure-track faculty positions (a cluster hire) at the rank of Assistant Professor with 60% research and 40% teaching appointment. Faculty will be members of one of these departments based on their disciplinary expertise and research interests: Animal and Avian Sciences, Environmental Science and Technology, Veterinary Medicine, Nutrition and Food Science, or Plant Science and Landscape Architecture. Depending on the department's needs, the exact split of the position's research and teaching responsibilities is negotiable at the time of appointment. The successful candidate will join a collaborative, interdisciplinary research community at UMD, with opportunities to collaborate with the AI Interdisciplinary Institute @ Maryland (AIM), Maryland Agricultural Experiment Station (MAES), and regional stakeholders involved in agricultural and environmental management for rural and urban ecosystems. Applicants may also be considered for a joint appointment with AIM. Ultimately, we seek individuals interested in applying AI to benefit Maryland residents and farmers in support of UMD's Land Grant mission. Candidates' disciplinary backgrounds could include, but are not limited to, agricultural engineering, agronomy, animal or avian science, aquaculture, computer science, environmental science, food science, horticulture, natural resources management, human or animal nutrition, plant science, biology, genetics, plant pathology, veterinary medicine, or related fields. Successful candidates will have experience/expertise applying AI in big data analytics, sensors, computer vision, robotics, remote sensing, precision agriculture, biological systems, molecular biology, precision nutrition, microbiome, wearable technology for health or performance monitoring, gene discovery, or other relevant technologies to solve current community/agriculture/environmental problems. Specific areas of research opportunity include:

• Utilizing AI to accelerate the discovery of strategies leading to improved health outcomes of humans, plants, animals, and the environment
• Application of AI-enabled surveillance or remote sensing systems, for monitoring and risk assessment in plant, animal, human, or natural ecosystems
• Applying AI to promote human health by increasing the nutritional value of foods and/or increasing food safety
• AI applications in precision agriculture to reduce production inputs
• Utilizing AI to accelerate gene discovery, programmed gene expression, and de novo protein design to develop new strategies/plants/vaccines for enhanced resistance to abiotic stressors and pathogens
• AI applications to support communication and policy analysis, sustainable design and green infrastructure planning, and ethics and governance across plant, animal, and/or environmental systems

More information about the departments of Animal and Avian Sciences, Environmental Science and Technology, Veterinary Medicine, Nutrition and Food Science, and Plant Science and Landscape Architecture, and existing faculty expertise and teams can be gleaned from their websites.

Position Responsibilities:

• Establish and maintain an externally funded research program in one or more research areas listed above.
• Develop and teach new courses in AI and data science applications in animal- and plant-based agriculture, environmental science and technology, veterinary medicine, or nutrition and food science at the undergraduate and graduate levels.
• Disseminate research findings through peer-reviewed publications and presentations at national and international conferences.
• Recruit and mentor graduate and undergraduate students.
• Provide academic advising for undergraduate majors and contribute to graduate education.
• Collaborate with faculty across departments, colleges, and external organizations to promote interdisciplinary research and outreach.
• Participate in departmental, college, and university service activities and governance.

Required Application Materials include (1) Cover letter outlining your interest in the position, including a statement of the department that would be a best-fit tenure home for you; (2) Curriculum Vitae; (3) a brief Research Statement highlighting research accomplishments and ongoing and future research goals; (4) a brief Teaching and Mentoring Statement detailing your teaching interests and experience (both within your home discipline as well as potential interdisciplinary teaching) and mentoring experience; 5) Published Scholarly Works that demonstrate your prior research experience using AI/ML in your discipline; and (6) a list of three Professional References. Requests for letters of reference will be made only for the candidates who are selected for final interviews.

Minimum Qualifications: Ph.D. in Animal Science, Agricultural Science, Environmental Science, Agricultural and Biological Engineering, Nutrition and Food Science, Veterinary Science, Data Science, Computer Science, Plant Science or Biology, Genetics, Horticulture, Agronomy, Plant Pathology, or related areas. Demonstrated experience developing and applying AI, ML, or data analytics to the above-mentioned research areas. Strong written and verbal communication skills. Evidence of scholarly publications in peer-reviewed journals. Potential to develop and sustain a funded, high-impact research program. Experience presenting research results at national or international meetings.

Preferred Qualifications: Experience applying innovative, data-driven approaches integrating AI, geospatial analysis, remote sensing, etc. in animal- and/or plant-based agriculture, environmental science and technology, veterinary medicine, plant science/biology, or nutrition and food science. Experience with programming languages (e.g., Python, R), AI/ML tools (e.g., TensorFlow, PyTorch), or GIS and remote sensing platforms. Teaching experience at the college or university level. Experience working collaboratively in interdisciplinary teams and engaging with agricultural and environmental stakeholders.