Assistant or Associate Professor: Precision Agriculture

• Develop a nationally recognized program through the development and use of precision agriculture technologies for crop management and contribute to the School of Agricultural and natural sciences goals improve agricultural productivity, health and resilience.
• Develop an extra-murally funded research program and publish outputs in refereed journals.
• Utilize precision agricultural technologies, climate-smart production techniques, artificial intelligence and controlled environment agriculture systems such as indoor/vertical farming to conduct translational research of value to stakeholders. Other potential areas include the use of robotic systems for high throughput phenotyping to generate large data on crop abiotic and biotic stressors, and its utilization for improving crop production.
• Work with other plant biology related faculty in the department and specialists in the areas of precision agriculture and remote sensing/GIS to create tools for identifying limiting factors in crop production.
• The candidate will also be involved in undergraduate and graduate instruction in their area of specialization that will add to the diversity of existing curriculum in areas of plant breeding, pathology, pest management and forestry. Mentor students in research activities and provide support to extension personnel in outreach activities.
• Performs other related duties as assigned.

• PhD in Agronomy, Agricultural and Biological Engineering, Machine learning, Geospatial systems or related areas.
• Note: Individuals with degrees outside of the US may be subject to verification at the expense of the candidate.
• Demonstrated ability to conduct a combination of fundamental and applied research of value to stakeholders.
• Demonstrated ability to work collaboratively on interdisciplinary teams.
• Experience in utilizing existing climate related data sets using high spatial and temporal resolution remote sensing from small unmanned aerial system (UAS) or low orbiting satellites and their application to agricultural production systems.

• Working experience or post-doctoral research in the areas of agricultural automation, agricultural robotics, precision agriculture, indoor and vertical farming is highly desirable.
• Experience in geospatial analysis, statistical analyses and machine learning, along with a familiarity in programming languages (R, C++, Python, etc.).
• Experience in developing and teaching courses in precision agriculture.
• Experience in using artificial intelligence and other digital agricultural technologies to predict outcomes in crop productivity is highly desirable.
• Demonstrated experience of working with extension personnel and effective communication with stakeholder groups for outreach activities.

• Ability to work independently and to be self-motivated.
• Excellent verbal and written communication skills.
• Critical thinking ability.
• Strong work ethics.

UMES is an EEO/AA employer and will not discriminate against any employee or applicant because of race, age, sex, color, sexual orientation, religion, national origin, marital status, genetic information, or political affiliation. Minorities, women, veterans, and persons with disabilities are encouraged to apply. The successful candidate must be able to show acceptable documentation establishing the right to accept employment in the United States of America without employer sponsorship.