Research Associate – Geospatial Data Analytics

Key Skills

Big Data Technology, Geospatial Statistical, GIS, Python Programming, R Programming

Job Description

Research Associate – Geospatial Data Analytics

Department of Animal Science

College of Agriculture and Life Sciences (CALS)

Cornell University

Ithaca, New York

This individual will be a Research Associate for the Cornell Nutrient Management Spear Program (NMSP; http://nmsp.cals.cornell.edu) in the Department of Animal Science. Specific focus will be on (1) evaluating the use of technology (Aerial imagery, elevation maps, crop scans, EC/EM mapping, statistical analyses, etc.) for estimating yield and determining yield stability, as well as delineation of soil management zones (soil biological buffer capacity-based zones); (2) analyzing remotely sensed data (aerial images from drone and satellites) and other sensors, such as yield monitors, EC sensors for yield model development and on-farm research, (3) working with big data analytics with past year yield data on a farm scale to develop yield models, and (4) developing machine learning and deep learning models with the sensor data to predict yield and yield stability zones. This position is expected to coordinate with NMSP leadership to document project results in the form of peer-reviewed journal articles, extension bulletins, and factsheets, as well as other extension materials and tools to assist in applied (field) research within the NMSP when needed. This individual will function as part of a multidisciplinary team with additional collaborators at the Rochester Institute of Technology, University of Buffalo, as well as the Statistical and Data Sciences Department at Cornell in the existing projects at NMSP and organize regular meetings with the collaborators.

This is a full time (100% FTE) position and will be located in Ithaca, New York. This is a three-year appointment with possible extension depending on available work, funding and performance.

Anticipated Division of Time

Data processing and reporting: 40%

• 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.

Data collection and management: 30%

• 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.

Mentoring students: 20%

• 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.

Personal and Professional Development: 10%

• 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.

Requirements

• 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.