Postdoc Associate

About This Role

K-State Olathe ((Use the "Apply for this Job" box below).) invites applications for a Postdoctoral Research Associate - AI & Computer Vision for Poultry Biosecurity to contribute to a USDA-funded research program. This is a 12‑month term, renewable annually for up to 2 years contingent upon funding. The immediate supervisor for this position will be Professor Majid Jaberi‑Douraki.

The purpose of this position is to develop an effective biosecurity strategy to protect commercial poultry meat and egg farms from infection with highly pathogenic avian influenza (HPAI) by reducing contact with wild birds and waterfowl that may carry the virus. The project will focus on preventing these wild bird species from approaching farm facilities, ponds, equipment, and animal housing areas where they may transmit HPAI to domestic flocks.

The Postdoctoral Research Associate will lead the visual data and analytics component of a field‑deployed deterrent system designed to safely repel wild birds from poultry operations.

To achieve this objective, we will deploy technical monitoring devices to identify and track the species, timing, and frequency of wild bird activity near commercial farms. In response to detected threats, automated deterrent systems will be activated to emit targeted sound, light, and/or motion‑based cues that safely repel birds without causing harm to either wild species or production poultry. The role will focus on establishing and analyzing visual surveillance zones around deterrent devices using trail camera systems and integrated device logs.

The Postdoc will apply artificial intelligence and classical statistical modeling approaches to classify bird species, quantify activity patterns, and evaluate behavioral responses to sound, light, and motion‑based deterrents. By integrating surveillance data with open‑source migratory bird information and local weather conditions, the position will identify effective deterrent combinations and develop a data‑driven decision matrix for alarm timing, frequency, and cue selection.

The postdoc will: apply AI and classical statistical models to analyze bird behavior and identify the most effective combinations of deterrent cues; develop a data‑driven decision framework for alarm timing, frequency, and cue type (sound, light, and motion) to optimize deterrent effectiveness; and contribute to the establishment of practical detection and response protocols for poultry producers.

All data will be securely stored on the 1

DATA platform, with field observations validated through manual annotation by trained graduate students.

Kansas State University Olathe, founded in 2011, is the newest campus in the K‑State system and serves Johnson County and the Greater Kansas City region. As a partner in the Johnson County Education and Research Triangle, the campus supports higher education through a unique local investment. K‑State Olathe focuses on industry‑ready education, professional development, applied research, and regional workforce needs, with programs and partnerships in areas such as food science, animal health, advanced manufacturing, supply chain, community health, and food as medicine.

Through academic programs, professional workshops, research facilities, and event space, the campus connects students, professionals, businesses, and community partners to education and innovation that create real‑world impact.

This position is Hybrid eligible. This role is expected to be performed on‑site approximately three days a week.

All employees must reside in the United States when they begin working to comply with state law. K‑State is unable to provide remote or hybrid work opportunities for residents of the state of Idaho.

Minimum Qualifications:

• Doctoral degree
• The degree requirement is necessary to ensure candidates possess the specialized knowledge, skills, and abilities that can only be attained through a formal educational program at this level.

Preferred Qualifications:

• Experience with AI, machine learning, or classical statistical modeling applied to behavioral or ecological data.
• Proficiency in analyzing…