• Analyze yield monitor data and use as ground truth to develop predictive models for yield estimation.
• Conduct literature searches, summarize data, and prepare reports, scientific articles, and visual aids.
• Evaluate clean yield data and it use for on-farm research evaluation and crop yield prediction.
• Evaluate sensor data for yield estimation and development of on-farm research approaches for use by farmers and farm advisors.
• Analyze on-farm testing approaches (spatial statistical analyses) using various data layers, including past yield, soil, and elevation.
• Analyze and evaluate sensor data (multispectral images from Unmanned Aircraft Systems - UAS and satellites) for yield model development and on-farm research.

• Collect data from different sources, such as yield monitors, remotely sensed images, GPS devices, and other available sources.
• Gather all data sources, overlay, and compile them into a big dataset.
• Extract information from all the data layers to make it suitable for further processing.
• Manage all the data sources and document the process.

• Mentor undergraduate students from agricultural sciences, statistics, and computer science to extract and analyze data.
• Guide them in developing automated workflows in Python and R.
• Train students on presentations, coding, data management, and documentation.

• Seek out and attend educational seminars and workshops as required by Supervisor.
• Continuously maintain all required educational/position qualifications to fulfill job requirements.
• Maintain good communications with supervisor, technical staff, postdoctoral associates, graduate students, temporary staff, and other collaborators within Cornell and at other institutions.
• Present research findings in conferences and extension meetings.

• Ph.D. in agronomy, agricultural engineering, computer science, and statistics with a focus on the integration of disciplines and systems analyses
• Expertise in computer software applications for database management, spreadsheets, word processing, and statistical analyses.
• Ability to program in Python and R and handle big datasets.
• Experience working with Geographic information system (GIS) and ability to develop automated pipelines for geospatial data layers.
• 3+ years of experience working in agricultural production and demonstrated understanding of applied soil fertility and/or nutrient management of forages for dairies, and analyses of on-farm research data.
• Must have excellent communication and leadership skills with the ability to prioritize multiple projects.
• Proven ability to work independently in collecting and summarizing data.
• Work independently and in collaboration with faculty/staff in the Department of Animal Science, School of Integrated Plant Science, and PRODAIRY, New York stakeholders, producers, and their advisors.
• Must be able to meet the travel requirements of the position and have reliable transportation, as well as have and maintain a valid and unrestricted New York State driver’s license.
• Familiarity with forage production systems and dairy farming preferred.

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