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!
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 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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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 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)
#J-18808-Ljbffr
Bioimage Analyst Arbeitgeber: University Of Zurich
Die Universität Zürich ist ein hervorragender Arbeitgeber, der eine dynamische und unterstützende Arbeitsumgebung bietet. Mit einem Fokus auf Mitarbeiterentwicklung und einer Vielzahl von Weiterbildungsmöglichkeiten fördert die Universität das Wachstum ihrer Angestellten. Zudem profitieren Sie von der zentralen Lage in Zürich, die nicht nur eine hohe Lebensqualität bietet, sondern auch ein inspirierendes Umfeld für innovative Ideen schafft.
