The Digital Pathology Research Group at the University of Bern (Group of Prof. I. Zlobec) takes a deep dive into the morphomolecular aspects and spatial biology of colorectal cancer using various computational and tissue visualization techniques in order to gain insights into tumor progression and dissemination and identify new predictive and prognostic biomarkers. We use digital pathology and artificial intelligence (AI) to investigate the multi-faceted phenomenon of “tumor budding” and the tumor microenvironment in colorectal cancer. Our group is enriched by the multi-disciplinary background of our students, our numerous industry, as well as national and international academic collaborators spanning the areas of pathology, immunology, oncology, machine learning and computer vision.
What is the position about?
We are currently establishing our multiplexed immunofluorescence platform at the Translational Research Unit, a core facility attached to the Digital Pathology Research Group. We are seeking a data/computer scientist or bioinformatician with a keen interest in spatial cancer biology who can analyze and translate such complex data into meaningful biological insights. These data will be combined with those from other modalities (morphological, molecular and clinical) to generate new biological understanding and clinically relevant perspectives into colorectal cancer.
- Analyzing high-dimensional multiplexed immunofluorescence data from tissue slides
- Supporting other team members of the Digital Pathology Research Group with data analysis
- Supervision of PhD students or Master students working on the related topic
- Presentation of results and participation in congresses internally, nationally, internationally
- Grant proposal writing and support
- Possible involvement in student lectures on AI in Medicine
We are looking for a talented post-doc with:
- A PhD in the field of computer science, bioinformatics, or similar
- Experience in computational image processing, ideally from histopathology images
- Experience with bioinformatics and biostatistical analysis (e.g. spatial proximity analysis, cellular neighborhood analysis, PCA, cluster analysis, graph approaches)
- Expertise in machine learning and deep learning in pathology is a major asset
- Expertise in R, Python, Matlab, TensorFlow / PyTorch
- Initiative to pursue own ideas
- Excellent communication skills in English (written and spoken)
- Interest in supervising students
- Keen to work as a member of the group
Start: as soon as possible
Salary: Competitive and according to the Swiss National Science Foundation
What we can additionally offer: you will be embedded in an internationally competitive translational and inter-disciplinary team at the University of Bern, Switzerland. You will work closely with clinical pathologists within our Institute of Pathology. You will have interactions with other partners and collaborators involved in our research group, including IBM Research, ZHAW, ETH Zurich, HES-SO Valais, HES-SO Fribourg and the Institute of Pathology, Zurich.
Application: Please send your application before April 15th 2022 including a short letter of interest, curriculum vitae with description of your professional experience, a list of publications, 2 references, and copies of the certificates of academic qualifications as a single pdf-file by Email to: email@example.com
University of Bern, Institute of Pathology, Human Resources, Murtenstrasse 31, CH-3008 Bern, www.pathology.unibe.ch
vor 12 Tagen geschaltet