Post Doctoral Scholar

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Job Title:

Department:

The AgSensing Lab in the Department of Food, Agricultural and Biological Engineering at The Ohio State University is recruiting a Postdoctoral Research Associate to conduct research at the forefront of precision agriculture and contribute to the development of innovative tools and methodologies that advance crop science and sustainable agricultural production. The successful candidate will play a key role in designing and implementing research at the intersection of sensor data collection, machine learning, remote sensing, and real-time agricultural decision-making. The candidate will contribute to projects focused on developing advanced machine learning models to quantify phenotypic and agronomic traits of crops, including corn, soybean, and other selected species. These models will leverage data collected from multiple sources, including unmanned aerial systems (UAS), satellite imagery, ground-based sensors, and other spatial and temporal datasets. The candidate will also contribute to the design, development, testing, and deployment of custom ground-based sensing platforms for efficient and accurate collection of agricultural data. These platforms will support integration of sensor systems and machine learning models for real-time or near-real-time decision-making, enabling scalable and actionable applications in agricultural production systems.

Areas of Responsibility

40% – Agricultural Data Analytics, Machine Learning, and Remote Sensing Develop, evaluate, and implement machine learning and data analytics approaches for quantifying crop phenotypic and agronomic traits. Process and analyze spatial and temporal datasets collected from UAS, satellite, ground-based sensors, and other sources. Integrate multi-source datasets and develop predictive models to support crop monitoring and agricultural decision-making.

25% – Sensor Systems and Ground-Based Platform Development Contribute to the design, development, testing, and deployment of ground-based sensing platforms for agricultural applications. Integrate sensors, data acquisition systems, and analytical models to enable efficient data collection and real-time or near-real-time decision-making. Conduct field testing and evaluate system performance under agricultural production conditions.

15% – Field Research, Data Collection, and Project Implementation Plan and conduct field experiments and coordinate collection of crop, sensor, UAS, and ground-truth data. Maintain research datasets, experimental records, and quality-control procedures. Support implementation of research activities and completion of project milestones and deliverables.

10% – Scientific Publications, Presentations, and Proposal Development Analyze and synthesize research findings and prepare manuscripts for peer-reviewed journals, conference presentations, technical reports, and project updates. Contribute to grant proposal development and identification of new research opportunities.

10% – Research Coordination, Mentoring, and Collaborative Activities Work collaboratively with interdisciplinary teams involving agricultural engineering, mechanical engineering, agronomy, computer science, soil science, and related disciplines. Provide technical guidance and research support to graduate and undergraduate students and assist with other research activities as needed.

Required Qualifications

Ph.D. in Agricultural Engineering, Electrical Engineering, Mechanical Engineering, Computer Science, or a closely related discipline. At least 5 years of relevant research experience in agricultural data analytics, remote sensing, machine learning, spatial data analysis, sensor systems, or related areas. Relevant experience obtained during Ph.D. research may be considered toward this requirement.

• Experience working with spatial, temporal, or remotely sensed datasets.
• Demonstrated experience developing or applying machine learning models.
• Proficiency in programming and data analysis using Python, R, or comparable analytical tools.
• Demonstrated ability in scientific writing, peer-reviewed publication, and technical communication.
• Strong analytical, organizational, problem-solving, and project-management skills.
• Ability to work independently and collaboratively within interdisciplinary research teams.

Preferred Qualifications

• Five or more years of experience using programming and data-analysis tools such as Python and/or R.
• Experience with UAS imagery, satellite remote sensing, GIS, or other geospatial datasets.
• Experience with agricultural production systems in the United States.
• Experience with crop phenotyping or precision agriculture applications.
• Experience integrating sensors, data acquisition systems, or robotic/ground-based platforms.
• Familiarity with real-time or edge-based data processing and decision-making.
• Experience conducting field experiments and collecting ground-truth agricultural data.
• Experience mentoring undergraduate or graduate researchers.
• Demonstrated experience contributing to grant proposals or externally funded research projects.

Expectations

The successful candidate is expected to publish research findings in international peer-reviewed journals, present results at professional conferences and project meetings, prepare regular project updates, contribute to grant proposal development, mentor graduate and undergraduate students, and support other research activities as needed. The candidate should possess strong analytical, technical, organizational, and planning skills and be able to work effectively both independently and as part of an interdisciplinary team. The position provides opportunities to collaborate with researchers in agricultural engineering, mechanical engineering, agronomy, computer science, soil science, and related disciplines.

Appointment

The position is initially expected to be a two-year appointment and may be extended based on satisfactory performance, continued funding, and programmatic needs. Salary will be commensurate with qualifications and experience. The position includes benefits in accordance with The Ohio State University policies, including health-care benefits.

Additional Information:

Interested candidates should submit a cover letter describing relevant research experience, technical skills, background, and research interests, along with a detailed current CV.

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Final candidates are subject to successful completion of a background check.  A drug screen or physical may be required during the post offer process.

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