Post Doctoral Scholar
Core
Develop and apply artificial intelligence methods for three-dimensional biological image data to turn volumetric and surface data into quantitative biological measurements for organismal and evolutionary biology research.
Role type
Postdoctoral researcher in 3D AI for biological imaging
Builds
Quantitative biological measurements from 3D imaging data (tomographic volumes, meshes, point clouds)
Domain
Biological imaging + Artificial Intelligence / Machine Learning
Deliverable
production ML models
Required skills
Python programming, deep learning frameworks (PyTorch), 3D data processing (volumetric images, meshes, point clouds), machine learning, computer vision, research methodology, technical writing
Preferred skills
volumetric image segmentation, foundation model adaptation, geometric deep learning, vision-language models, high-performance computing, open-source software contribution
Technologies
PyTorch, Python
Responsibilities
Evaluate and adapt promptable/automated segmentation models for volumetric biological imaging; develop methods for initializing and propagating segmentations across specimens; design evaluation protocols for method performance; contribute to 3D shape analysis or multimodal/generative approaches to 3D biological data; release working code and document methods for reproducibility
Seniority
Postdoctoral Scholar (early-career researcher)
