The NSF Imageomics Institute at The Ohio State University is seeking a Postdoctoral Scholar in 3D Artificial Intelligence for Biological Imaging, offering a unique opportunity for researchers working at the intersection of computed tomography, biological imaging, machine learning, and quantitative morphology. The position is jointly supervised by A. Murat Maga (University of Washington and Seattle Children’s Research Institute) and Tanya Berger-Wolf, as part of the Institute’s 3D Convergence Working Group.
This role will be of particular interest to members of the CT and digital morphology community who are interested in developing next-generation tools for extracting biological information from increasingly large collections of volumetric imaging data. As CT scanning, photogrammetry, and other 3D imaging approaches continue to generate vast datasets, there is a growing need for automated, scalable analytical methods that can transform scans into biologically meaningful measurements.
Applications are being reviewed immediately and will continue until the position is filled. The appointment is a one-year, full-time position with an immediate start available.
Research Focus
The postdoctoral researcher will contribute to projects centered on:
- AI-driven segmentation of volumetric biological imaging datasets.
- Adaptation of foundation models for biological CT and other volumetric imaging modalities.
- Atlas- and template-based approaches for propagating segmentations across large specimen collections.
- Development of rigorous benchmarking and validation approaches that identify both strengths and failure modes of AI methods.
Additional opportunities exist in:
- 3D geometric morphometrics and shape analysis.
- Machine learning on meshes, point clouds, and landmark datasets.
- Automated landmarking and specimen correspondence.
- Multimodal AI linking 3D structure with text and images.
- Generative models of biological form.
Ideal Candidates
Applicants should hold (or be nearing completion of) a PhD in computer science, biomedical engineering, applied mathematics, statistics, quantitative biology, or a related field. Competitive candidates will have experience in machine learning, computer vision, Python programming, and working with 3D data such as CT volumes, surface meshes, or point clouds.
For CT imaging researchers, experience with volumetric segmentation, biological imaging datasets, geometric deep learning, statistical shape analysis, or open-source scientific software development will be especially relevant.
Why This Matters to the CT Community
This position highlights a rapidly growing area in the imaging sciences: the integration of artificial intelligence with high-resolution 3D biological datasets. The successful candidate will help develop tools capable of scaling analyses from dozens to thousands of CT-scanned specimens, enabling new approaches to comparative anatomy, evolutionary biology, biodiversity research, and biomedical imaging.
Learn More and Apply
- Job Posting: Ohio State University Postdoctoral Scholar Position
- NSF Imageomics Institute: Imageomics Institute Website
- Imageomics Team: Meet the Team
- A. Murat Maga Lab: Faculty Website
Know a recent PhD or advanced graduate student looking to apply AI methods to biological CT data? Please consider sharing this opportunity.