Job Description

The Research Associate will oversee the setup, calibration, and maintenance of all Precision Livestock Farming (PLF) tools. This includes managing the integration of data from various PLF systems and ensuring compliance with data management protocols, contributing to the overall quality and reliability of research project. Tasks and Responsibilities: PLF System Management: Setup, calibrate, and maintain PLF tools, including IoT-based sensors, automated monitoring systems, and precision handling equipments. Ensure PLF systems are functioning correctly and producing reliable data. Regularly update software and firmware for PLF tools and troubleshoot system errors. Manage the collection, storage, and integration of data from various PLF systems. Ensure data security and adherence to established data management protocols. Conduct preliminary analysis to validate PLF-generated data before research applications. Conduct preventive maintenance and troubleshooting for PLF-related equipment. Utilize PLF technologies to monitor livestock behavior, welfare, and health in real time. Implement and optimize automated monitoring systems for feed intake, locomotion, and physiological indicators. Work on predictive modeling and AI-based analytics for decision-making in livestock management.



Minimum Qualification



Bachelor's in computer science or related fields



Preferred Qualification



Certificate of Advanced PLF Technologies and Applications Expertise in PLF tools and techniques, including sensor technology, automated livestock monitoring, and data-driven decision-making. Proficiency in software used for PLF applications, such as MATLAB, Python, R, or cloud-based data analytics platforms. Strong background in livestock production, animal behavior, and welfare monitoring. Experience in big data analysis and machine learning models for livestock performance optimization. Ability to integrate IoT devices, real-time sensors, and camera-based monitoring systems into research projects. Strong communication and training skills to educate faculty members and students on PLF technologies. Experience in developing predictive models for disease detection, reproductive performance, and feed efficiency. Excellent IT skills and ability to manage large datasets effectively.



Expected Skills



Minimum 5 years of experience in PLF technology applications in livestock farming R&D research experience at least 2 projects, Project records



Salary Range



based on negotiation



Close Date Kindly apply before the closing date.



01/04/2025