Research Engineer Lead

Kansas State University; Manhattan (KS); On-site; USD 65,000 - 100,000; Full time

Job summary

Kansas State University’s Farmslab team seeks a scientist to integrate agricultural engineering, agronomy, GIS, remote sensing, and data science, building scalable analytical workflows and research software for complex agricultural datasets.

You will develop backend and frontend workflows using Python, R, SQL, GIS, and cloud platforms, lead interdisciplinary teams, and translate stakeholder needs into practical software features and dashboards.

Qualifications

• PhD or veterinary medicine degree with strong research training and publication record.
• Minimum three years of relevant research experience in digital agriculture or related fields.
• Ability to translate user needs into technical specifications and practical software features.

Responsibilities

• Design, develop, test, validate, and implement scalable analytical workflows and software.
• Develop automated data-ingestion, cleaning, transformation, analysis, and visualization pipelines.
• Lead interdisciplinary teams and coordinate external collaborators on grant projects.
• Translate breeder, researcher, and producer needs into software features, dashboards, reports and maps.
• Prepare technical documentation, training materials, and demonstrations for workshops.

Skills

Python

R

SQL

GIS

Cloud computing

Version control

Reproducible workflows

Machine learning

Deep learning

Computer vision

Time-series analysis

Dashboard tools

Education

PhD or Doctorate (PhD or DVM)

Tools

Streamlit

R Shiny

Tableau

Power BI

GIS software

Job description

About This Role

This position will integrate agricultural engineering, agronomy, GIS, remote sensing, image analysis, statistics, data science, machine learning, GeoAI, generative AI, and software development. The scientist will design, develop, test, validate, and implement scalable analytical workflows and research software for processing complex agricultural datasets, including field-trial, genotype, phenotype, yield, weather, soil, pest, disease, scouting, crop-management, UAV, satellite, sensor, GPS/GNSS, machinery, and experimental-design data. The position will develop automated backend and frontend workflows for data ingestion, cleaning, standardization, transformation, spatial and tabular integration, analysis, visualization, reporting, and export using Python, R, SQL, GIS, cloud-computing platforms, and reproducible software-development practices. Responsibilities will include developing and validating statistical, agronomic, remote-sensing, machine-learning, deep-learning, computer-vision, image-segmentation, time-series, and decision-support methods for trait prediction, yield estimation, crop monitoring, breeding decisions, site-specific management, and crop-management recommendations. The scientist will also support field research involving geospatial field layouts, experimental and strip-trial design, treatment geolocation, sampling protocols, ground-truth data collection, soil and plant sampling, UAV operations, GPS/GNSS systems, remote-sensing sensors, precision-agriculture equipment, and agricultural field machinery. The position will evaluate software functionality, accuracy, usability, scalability, and reproducibility; compare analytical capabilities with established GIS and agricultural software platforms; and translate breeder, researcher, producer, and industry needs into practical software features, technical specifications, reports, dashboards, maps, and actionable recommendations. The successful candidate will independently manage complex projects, provide technical leadership to interdisciplinary teams, contribute to proposal and grant development, build collaborative relationships, identify funding and partnership opportunities, develop technical documentation and training materials, and lead workshops, software demonstrations, surveys, stakeholder meetings, and technology-dissemination activities. Approximately 80% of the position will focus on research, data analysis, model and software development, field activities, technical management, testing, and validation, while approximately 20% will focus on collaboration, extension, communication, stakeholder engagement, outreach, training, and technology dissemination.

About Us

The Farmslab team is part of the Department of Biological and Agricultural Engineering in the Carl R. Ice College of Engineering at Kansas State University. The team conducts interdisciplinary research in digital agriculture, precision agriculture, geospatial analytics, remote sensing, high-throughput phenotyping, agricultural data science, automation, sensing technologies, and decision-support systems. Farmslab works closely with faculty, students, producers, plant breeders, agronomists, agricultural engineers, statisticians, software developers, commodity organizations, government agencies, research institutions, technology companies, and agricultural industry partners. The team develops practical and scalable research solutions that improve agricultural data collection, analysis, visualization, interpretation, and decision-making. The position will contribute to ongoing development and implementation of Plotlytix and related analytical tools designed to simplify geospatial and agricultural data workflows. These efforts support researchers, breeders, producers, and industry collaborators by reducing fragmented data-processing steps and improving reproducibility, collaboration, accessibility, and timely decision-making. Kansas State University is a land-grant institution with strong programs in agriculture, engineering, research, extension, and stakeholder engagement. The university provides opportunities to collaborate across departments, research centers, extension programs, commodity groups, government agencies, and agricultural industries.

Worksite Description

This position is On-site.

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.

What You'll Need to Succeed

Minimum Qualifications

• Requires a doctor of philosophy or veterinary medicine and three years of relevant experience. The degree requirement ensures candidates possess the research design expertise, data analysis proficiency and methodological rigor necessary to plan and execute studies, coordinate data collection and prepare documentation for publication. These competencies are typically developed and rigorously validated only through the comprehensive curriculum and intensive experiential experience inherent in a formal degree program.
• Valid Driver's License

Preferred Qualifications

• Doctoral degree in agricultural engineering, biological systems engineering, agronomy, geography, remote sensing, data science, statistics, or a closely related field.
• At least 3 years of relevant experience in the following areas: precision agriculture, digital agronomy, plant breeding, high-throughput phenotyping, crop consulting, geospatial analysis, remote sensing, agricultural statistics, field research, agricultural data science, or analytical software development.
• Experience conducting applied research in digital agriculture, precision agriculture, plant breeding, phenotyping, crop production, or soil and water management.
• Experience working with UAV, satellite, GIS, GPS/GNSS, sensor, machinery, environmental, and agricultural field-trial datasets.
• Proficiency in Python, R, SQL, GIS, cloud computing, version control, and reproducible data-analysis workflows.
• Experience developing or testing geospatial, statistical, agricultural, or analytical software.
• Experience with raster processing, vector analysis, image analysis, remote sensing, spatial statistics, and database integration.
• Experience with regression, classification, clustering, machine learning, deep learning, time-series analysis, computer vision, image segmentation, or Bayesian methods.
• Experience using machine-learning and deep-learning frameworks.
• Experience with dashboard and visualization tools such as Streamlit, R Shiny, Tableau, Power BI, or comparable platforms.
• Knowledge of experimental design, agricultural statistics, crop growth stages, agronomic practices, yield-limiting factors, pest and disease management, nutrient management, irrigation management, soil and water management, and field variability.
• Experience supporting agricultural field research, UAV operations, GPS/GNSS systems, crop and soil sampling, sensors, and precision-agriculture equipment.
• Experience leading interdisciplinary projects and coordinating technical teams and external collaborators.
• Experience with grant writing, proposal development, technical reporting, scientific writing, workshops, demonstrations, or extension activities.
• Ability to translate user and stakeholder needs into technical specifications and practical analytical solutions.
• Strong written, verbal, analytical, organizational, project-management, and interpersonal skills.
• Ability to communicate technical findings to scientific, industry, producer, and public audiences.

Additional Role Information

• Ability to work independently and collaboratively in interdisciplinary research and software-development environments. Ability to travel to agricultural research sites, stakeholder meetings, workshops, conferences, and partner locations, with anticipated travel of less than 10%. Ability to work outdoors under variable field and weather conditions and to operate or work around UAV systems, GPS/GNSS equipment, agricultural sensors, computers, and field-research equipment. A valid driver's license, or the ability to obtain one, may be required for university business travel.

Sponsorship eligibility

This position is eligible for sponsorship.

Application Window

Applications close on: August 25, 2026

Anticipated Hiring Pay Range

$64,709 - $100,244 annual pay rate