Bioimage Analyst

The successful candidate will: develop OME-Zarr conversion workflows tailored to flow cytometry imaging data • design and implement novel components for Fractal addressing common use-cases identified together with the Flow Cytometry Facility, including AI-based segmentation and morphological feature extraction • validate the pipeline on biological applications, in close collaboration with UZH researchers • produce high-quality documentation, tutorials, and training materials to ensure the uptake of these tools by the UZH research community • contribute to the scientific dissemination of the work through publications, presentations, and community engagement within the Fractal and OME-Zarr ecosystems

We are looking for a motivated scientist with strong computational skills and a genuine interest in bridging advanced image analysis and biology. Furthermore, you should bring the following qualifications: a master's degree or PhD in computational biology, bioinformatics, computer science, biomedical engineering, physics, or a related field • strong programming skills in Python, including experience with scientific libraries for image analysis (e.g. scikit-image, numpy, dask) and familiarity with version control (Git) • experience with bioimage analysis, ideally including AI-based segmentation methods • familiarity with modern image data standards such as OME-Zarr, or a clear willingness to learn them • experience in having mastered a biological project involving microscopy/flow cytometry data is an advantage but not required • the ability to work independently as well as collaboratively across interdisciplinary teams (computational and experimental) • excellent communication skills in English (German is not required)