Postdoc Associate
About This Role
K-State Olathe 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 artificial intelligence 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 1DATA platform, with field observations validated through manual annotation by trained graduate students.
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 visual data from cameras or video surveillance systems.
- Strong programming skills (e.g., Python, R, MATLAB, or similar) for data processing, modeling, and visualization.
- Experience integrating multi-source datasets (e.g., environmental, sensor, and field observation data).
- Knowledge of avian biology, wildlife behavior, or biosecurity in agricultural systems.
- Experience with database management, secure data storage, and collaborative research platforms.
- Ability to work independently and collaboratively in a multidisciplinary team.
- Strong written and oral communication skills, including the ability to present findings to diverse audiences.
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