Assistant Professor - AI Agriculture and Natural Resources; tenure-track

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JR 103283

Appointment type: 9-month tenure-track faculty

Salary range: $95,000 - $110,000

The University offers a comprehensive benefits package.

Anticipated start date: August 2026

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. As part of the College of Agriculture and Natural Resources Cluster Hire, the Department of Animal and Avian Sciences at the University of Maryland, College Park seeks candidates with expertise in applying AI and principles of precision agriculture to improve animal systems.

Research focus areas may include, but are not limited to: animal behavior, health, and welfare; nutritional and reproductive efficiency; resilience to climatic stress; and reduction of environmental impacts. The candidate’s AI‑driven research will complement the department’s current strengths in reproduction and development, genetics/genomics, nutrient utilization, and infectious disease.

Applications are invited for one or more tenure-track faculty positions (a cluster hire) at the rank of Assistant Professor with a 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 at 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.

• 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…