The imaging-in-plants Postdoctoral Scholar will serve in the Division of Biostatistics, College of Public Health, at The Ohio State University and is responsible for executing statistical and computational research activities focused on novel methods development for processing, segmentation, and trait extraction from 3D CT images of plant roots under the mentorship and training of the assigned faculty supervisor. This role requires a solid foundation of discipline‑specific knowledge in plant physiology, CT imaging, and deep learning/AI, and the ability to generate innovative ideas and novel lines of inquiry that contribute to the team’s scientific objectives. The postdoctoral scholar will design and execute experiments logically and efficiently, interpret data accurately, and apply appropriate analytical approaches to support research conclusions. The position requires effective use and understanding of plant physiology, high performance computing, maintaining accurate and thorough research records and code documentation, and staying current with new techniques and emerging methodologies. Ongoing engagement with scientific literature is essential to inform experimental design, support project development, and ensure alignment with current best practices in the field. This role will lead and/or contribute to the dissemination of research findings through the preparation of manuscripts and giving presentations of findings at professional conferences in plant phenotyping. The postdoctoral scholar will approach their work collaboratively, valuing constructive mentorship, open exchange of ideas, and active participation in the intellectual life of the unit. This role may include the training and mentorship of early career scientists in the research group, engaging with community partners and external research collaborators, and participating in grant writing, service, and/or teaching-related activities that support the team’s overall scientific objectives and postdoctoral scholar’s professional development. This position will end on or before May 31, 2027, with possibility of renewal based on continued availability of funding and performance.
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Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree