The Image Analysis Postdoctoral Training Program is an opportunity for biologists with strong interest and some experience in image analysis to develop deeper skills through many different individual projects as well as by supporting thousands of researchers around the world who are accomplishing great things with our lab’s open-source software, CellProfiler, and our deep learning-based tools in development. Quantitative image analysis is an under-served need in the biological community, and our group has passion and experience in both creating the tools to make it easier to do and training researchers to do it well.
Selected candidates will be trained over 2-3 years to develop their image analysis, software engineering, data science, and project management skills in concert; they will decide their own focus in skill development while advancing important biomedical projects around the globe. “Graduates” will be well-suited for positions providing or leading image analysis services for a central microscopy facility in academia or the biotech/pharma industry. Work in this training program will have two main dimensions:
- Deep impact, on important biomedical research projects: Develop image analysis solutions, working in-depth with brilliant biomedical researchers to push forward the boundaries of what can be extracted from high-throughput imaging experiments. We collaborate with dozens of biomedical research laboratories to identify disease states, potential therapeutics, and gene functions from microscopy images.
- Broad impact, supporting the bioimage analysis community: Support thousands of biologists worldwide by answering questions about CellProfiler and other tools we create at our popular online forum. Deliver educational workshops (including travel if desired) on image analysis and open-source software tools.
For more information, contact us.
Hiring for this program takes place during open calls held once to twice per year, as dictated by funding and graduation of current members. The last call for this program closed in March of 2023.