Job Title
Research Associate Professor/Research Professor & Assistant Director, Artificial IntelligenceAgency
Prairie View A&M University
Department
Cooperative Agricultural Research Center
Proposed Minimum Salary
Commensurate
Job Location
Prairie View, Texas
Job Type
Faculty
Job Description
The Cooperative Agricultural Research Center (CARC) at Prairie View A&M University seeks qualified candidates for the Research Associate Professor or Professor and AI in Agricultural Research Leader position. This pivotal role is designed to advance the Artificial Intelligence Research Program by implementing innovative and strategic methodologies that address immediate and long-term challenges. The focus will include resolving critical issues concerning providing nutritious and healthy food for the world's expanding population.
The incumbent will spearhead a distinguished AI research team supporting underserved producers and businesses by developing and applying safe, productive practices. This role will involve pioneering efficient, innovative, evidence-based solutions within agriculture, food systems, nutrition, and environmental management. The research will incorporate advanced technologies such as high-resolution sensing systems and autonomous robotics to improve precision and operational efficiency in agricultural processes. Furthermore, sophisticated data analytics and machine learning algorithms will extract actionable insights from large and complex datasets, enhancing predictive capabilities and optimizing decision-making.
The incumbent will integrate AI-driven technologies into climate-smart solutions that empower underserved communities and foster their development. By leveraging state-of-the-art AI methodologies with sensing technologies, robotics, and data analytics, the role will advance food and agricultural systems, thereby improving all Americans' health, nutrition, and quality of life while contributing to global food security. The incumbent will also build a research team focused on innovative innovations that enhance food safety, address food insecurities, and promote nutritional security.
Areas of research expertise and interest. We seek candidates with research expertise in advanced Artificial Intelligence technologies across agriculture, animal science, and food science. Key areas include precision agriculture, AI-driven pest and disease management, automated irrigation and nutrient optimization, AI applications in animal science, and AI innovations in food science. Precision agriculture leverages AI technologies like machine learning, computer vision, and remote sensing to enhance field management and productivity. AI-driven pest and disease management uses neural network-based systems for early detection and mitigation, promoting sustainability. Automated irrigation and nutrient optimization employ AI for dynamic scheduling and predictive analytics, improving efficiency and soil health. AI enhances livestock management and welfare through predictive models and advanced monitoring in animal science. AI in food science advances safety, quality, and processing through real-time monitoring and predictive analytics. These research areas provide the incumbent opportunities to engage in innovative projects addressing critical challenges and driving innovation across agriculture, animal science, and food science.
The AI in Ag System Leader, in collaboration with the Executive Associate Director (EAD) of the CARC, the Assistant Director of CARC, and the Associate Dean (AD) for Academic Programs, will establish the overall vision and oversee the operational management for the AI in Ag system in regards to research priorities and the general development of research scientists (including faculty with split teaching-research appointments and research faculty), postdoctoral fellows, research specialists and technicians, and student research interns within the Plant Systems. As the chief administrative officer of the AI in Ag System Research Program, the leader has the responsibility for the delivery of a robust program of research and related activities by CAFNR and the CARC regarding mission goals and objectives as spelled out in the PVAMU, CAFNR, CARC, Cooperative Extension Program (CEP) as well as the USDA/NIFA strategic plans. This position will involve the day-to-day management of staff and resources and operational strategies for the unit.
The position will support the work of AI in Ag System research scientists who are engaged in the growth of plants in field plots and greenhouse settings. It is pivotal for advancing research, education, and innovation in AI in Ag.
This position is funded by a grant or restricted funds. Continued employment is contingent on the renewal of grant or restricted funding.
Responsibilities:
Required Education and Experience:
Required Knowledge, Skills, and Abilities:
Other Requirements:
Preferred Qualifications:
Job Posting Close Date:
Required Attachments:
Please attach all required documents listed below in the attachment box labeled as either “Resume/CV or Resume/Cover Letter” on the application. Multiple attachments may be included in the “Resume/CV” or Resume/Cover Letter” attachment box. Any additional attachments provided outside of the required documents listed below are considered optional.
Application Submission Guidelines:
All applicants are required to apply via our Career Site on or before the closing date indicated on the job posting. Applicant inquiries received via email and websites such as Indeed, HigherEdJobs, etc. will not be considered unless the individual has applied to the available position via the PVAMU Career site.
The required documents listed in the above "Required Attachments" section must be attached to the application prior to the job closing date indicated to ensure full consideration for the application submitted. Please contact the Office of Human Resource on or before the closing date indicated above at 936-261-1730 or jobs@pvamu.edu should you need assistance with the online application process.
Background Check Requirements:
All positions are security-sensitive. Applicants are subject to a criminal history investigation, and employment is contingent upon the institution’s verification of credentials and/or other information required by the institution’s procedures, including the completion of the criminal history check.
Equal Opportunity/Affirmative Action/Veterans/Disability Employer.
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