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Bioimage Analyst

Job in 8424, Embrach, Kanton Zürich, Switzerland
Listing for: University of Zurich
Full Time position
Listed on 2026-06-03
Job specializations:
  • Research/Development
    Research Scientist, Data Scientist, Biomedical Science, Biotechnology
Salary/Wage Range or Industry Benchmark: 30000 - 80000 CHF Yearly CHF 30000.00 80000.00 YEAR
Job Description & How to Apply Below
Location: Embrach

Your responsibilities

  • 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)
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