Post Doctoral Scholar

Post Doctoral Scholar

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.

• PhD in Statistics, Engineering, or related discipline with experience developing or using image processing and segmentation software and AI models.
• Experience coding in python and using plant root segmentation software
• Experience segmenting 3D CT images in plant sciences
• Experience with high performance computing/high throughput computing resources for research
• Evidence of previous relevant research publications.
• Strong scientific writing skills, experience in manuscript preparation, and the ability to communicate research in scientific posters and presentations are essential.

• Candidates should have experience working and developing with py Torch
• Experience with distributed and high-throughput computing and the SLURM scheduler
• Knowledge of plant phenotyping

Pay Range: $62,232-$70,000 annual estimated base salary

Salary will be based off of education, experience, internal equity, and budget allowance.

60%:
Research and Computational Work:
Lead and support studies of novel AI methods for 3D CT image pre-processing, segmentation, and trait extraction informed by knowledge of root physiology and root system architecture.

20%:
Scientific communication:
Lead and support the preparation and submission of manuscripts resulting from the research and quantitative work. Lead and support the preparation and presentation of the research and results via scientific posters, oral presentations, and seminars.

15%:
Research Operations and Technical Support:
Help manage the research project by organizing, storing, and working with images and metadata collected by other researchers. Support the implementation of hardware and software, standard operating procedures, and contribute to the optimization of workflows.

5%:
Other special projects and duties to support departmental and team research work as assigned.

Cunz Hall (0293)

Term (Fixed Term)

40

First Shift

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

The university is an equal opportunity employer, including veterans and disability.