Bioimage Analyst 100 %

Description du poste

### The University of Zurich, Switzerland's largest university, offers a range of attractive positions in various subject areas and professional fields. With around 10,000 employees and currently 12 professional apprenticeship streams the University offers an inspiring working environment on cutting-edge research and top-class education. Put your talent and skills to work with us. Find out more about UZH as an employer! ### Your responsibilities 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 Your profile 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)