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Assistant Professor of Precision Agriculture Technologies and Data Management (Research/ Extension),

Employer
Virginia Tech
Location
Blacksburg, Virginia (US)
Salary
Commensurate with qualifications
Closing date
May 27, 2021

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Discipline
Life Sciences, Agricultural Science, Physical Sciences, Engineering
Position Type
Full Time
Job Type
Faculty
Organization Type
Academia

Assistant Professor of Precision Agriculture Technologies and Data Management (Research/ Extension), Tenure Track

Virginia Tech’ s College of Agriculture and Life Sciences (CALS) is seeking applicants for a 12-months tenure track faculty position in Precision Agriculture Technologies and Data Management (Research/Extension) as part of its Phase II SmartFarm Innovation NetworkTM faculty cluster hire. Phase II includes a total of seven (7) faculty positions to be filled within several academic units and Agricultural Research and Extension Centers. Collaborations of cluster hires and existing faculty will enhance interdisciplinary flagship programs at the nexus of digital, biological, social, and physical sciences and engineering with application to agriculture, food, and natural resources. The cluster hire will be affiliated with the Center for Advanced Innovation in Agriculture for enhancing interdisciplinary networking. This ambitious vision will create a statewide network of interconnected faculty, partners, and resources for scientific discovery and developing, deploying, and extending new technologies. The goal is to increase overall productivity, resiliency, sustainability, and economic value of food, agriculture production systems, and natural resources and expand Virginia Tech’s global influence in this rapidly evolving domain.

Description: The successful candidate will develop a nationally recognized research and Extension program in precision agriculture technologies and data management. The tenure home will reside either in the School of Plant and Environmental Sciences or the Department of Biological Systems Engineering. The position will be located at the Tidewater AREC in Suffolk, VA. Linkages with colleges and departments outside of CALS and with relevant industry are highly encouraged. Opportunities for international engagement exist and are encouraged.

The Extension program will provide guidance and training for Virginia’s agricultural producers, county Extension agents, industry and researchers to better manage and optimize crop production efficiencies using data science and precision agriculture technologies. Integration of research and Extension programs will enhance development, adoption and utilization of precision agriculture applications and data science to increase agricultural resiliency and sustainability. Examples of applications and technologies include, but are not limited to, remote sensing, unmanned aerial vehicles (UAV), precision irrigation/fertigation systems, smart sensor design, computer vision, GPS/GIS data for site specific management, wireless sensor networks, data science/analytics for agricultural applications, and autonomous/robotic systems in agronomic/horticultural cropping systems.  The broad goal is to contribute to a statewide agriculture data and technology network including the main campus at Blacksburg, the various ARECs, and county-level Virginia Cooperative Extension offices to provide the agricultural community of the Commonwealth access to digital information that enhances a new agricultural and natural resources’ economy.

The successful individual is expected to secure extramural funds to support an integrated Extension and research program. Strong communication and interpersonal skills are required, and the candidate is expected to establish and maintain close working relationships with industry, commodity groups, state agencies, county Extension agents, regional Extension specialists, and other organizations as appropriate. The development of a focused and cohesive research and Extension precision agriculture program that addresses the needs of producers in Virginia and the region and supports the publication of peer-reviewed Extension materials, popular press articles, and refereed scientific articles is required. The successful candidate is also expected to recruit and mentor graduate students.

In addition to the online application (https://jobs.vt.edu, job number 515772) required application materials include:  1) cover letter summarizing qualifications, 2) curriculum vitae, 3) statement of current research interests (1-page limit), 4) statement of extension education and graduate mentoring philosophy (1-page limit), and 5) full contact information for four professional references. All inquiries concerning this position should be directed to the Search Committee Chair, Dr. Maria Balota, mbalota@vt.edu (757-807-6538). Review of applications will begin on June 10, 2021 and will continue until a suitable candidate is selected.

Required Qualifications: A PhD in biological systems engineering, agricultural engineering, mechanical engineering, agronomy or a closely related field is required.

Preferred Qualifications:

  • Experience in precision agriculture research and Extension
  • Knowledge of current and emerging technologies in precision agriculture
  • Experience in agronomic and/or horticultural cropping systems
  • Ability to effectively communicate with industry and producer stakeholders
  • Demonstration of success in securing extramural funding and publication of research results

Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, national origin, political affiliation, race, religion, sexual orientation, or veteran status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.

If you are an individual with a disability and desire accommodation please contact the hiring department.

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