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22.05.2020

Image analysis, bioinformatics and machine learning in pathology 60%

  • 8091Zürich
  • Teilzeitstelle 60%

Das USZ steht jeden Tag allen Menschen offen und bietet medizinische Grundversorgung und Spitzenmedizin an zentraler Lage in Zürich. Wir nutzen unseren universitären Wissensvorsprung, um verschiedenste Gesundheitsprobleme zu lösen: nah am Menschen, hochspezialisiert und auf dem neuesten Stand der Forschung.
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Das UniversitätsSpital Zürich löst Gesundheitsprobleme – auch sehr komplexe. Dafür nutzen wir unseren universitären Wissensvorsprung: Von neuen Erkenntnissen profitieren unsere Patientinnen und Patienten als erste.
Jährlich vertrauen über 35‘000 stationäre und 134‘000 ambulante Patientinnen und Patienten unserem Spital und seinen über 8‘000 Mitarbeitenden. Es ist damit ein führendes Spital der Schweiz.
Dank der interdisziplinären Zusammenarbeit unserer über 40 Kliniken und Institute sowie der Nähe zu UZH und ETH machen wir neustes Wissen verfügbar und bieten aktuellste Therapien für vielfältige Gesundheitsprobleme.

Image analysis, bioinformatics and machine learning in pathology 60%

Zürich

Job description

Understanding the differences between healthy and diseased tissues is key for the development of new therapies. Digital pathology is a new field in medicine making morphologic information accessible at unprecedented scale for research and technology development. We are looking for a highly ambitious and dedicated applicant with research experience in digital pathology, digital image analysis and advanced machine learning to take on a section lead within the Quantitative and Digital Pathology Group at University Hospital of Zurich. The successful applicant will lead their own research focus, will help to build research group capacity, engage in national and international collaborations and implement AI algorithms into diagnostic practice.

Your responsibility

  • Section lead of a digital pathology focus area.
  • Promote the development of digital pathology at Zurich University Hospitals
  • Participate in national and international collaborations involving academia and industry
  • Project-specific development of image analysis and machine learning algorithms for disease classification and patient stratification
  • Post-doc fellows with exceptional qualifications may be granted responsibility for co-supervising MSc, PhD, or MD students on a subject related to their research.
  • Scientific publications and presentations at national and international conferences are expected.

Your profile

  • PhD in computer science, engineering, bioinformatics, natural science, biomedical science, statistics, or applied mathematics
  • Prior research experience of 1-2 years using advanced machine learning for image analysis, ideally on histopathological images.
  • Prior experience with handling of genomic data is of advantage.
  • Experience statistical data analysis and visualization
  • Track record of high quality publications with at least one first-author paper in a peer-reviewed journal.
  • Excellent analytical, communication and writing skills; ability to professionally communicate with scientific and lay audiences.
  • Interest in real-life application of image analysis to diagnostics
  • Excellent English language skills are required

Our offer

We offer an interdisciplinary post-doctoral position connecting digital pathology with bioengineering and clinical science at the Institute of Pathology and Molecular Pathology, University of Zurich. The position will be directly supervised by the Prof. Viktor Kölzer, lead for digital pathology at Zurich University Hospitals. In Zurich, you will be immersed in a dynamic, open and motivating academic environment. We are supported by intra- and extramural funding and are involved in several high-visibility national and international academic and industry collaborations (University of Oxford, University College London, University of Leiden, ETH Zurich, University of Bern, University of Basel, Palleon Pharmaceuticals, Roche, IBM Research).

For informal inquiries, please contact Prof. Dr. Viktor Koelzer.

viktor.koelzer@usz.ch.

We look forward to receiving your online application

Über das USZ

The University of Zurich is a leading center for several important developments in precision medicine including tumor genomics, proteomics and digital medicine. The Quantitative and Digital Pathology Group is spearheading the digitalization of pathology for the analysis of diagnostic tissue samples from clinical workflows and experimental cancer research. The Institute of Pathology and Molecular Pathology is centrally located in Zurich city, one of the most highly ranked cities in regards to safety and living quality in the world. The diagnostic services are fully accredited and are working with the latest technology standards in all areas. The Institute includes tissue pathology / cytology / post-mortem / neuropathology departments, a state-of-the-art molecular pathology laboratory, tissue research facility, centralized tissue bank and cancer registry.

Universität
Understanding the differences between healthy and diseased tissues is key for the development of new therapies. Digital pathology is a new field in medicine making morphologic information accessible at unprecedented scale for research and technology development. We are looking for a highly ambitious and dedicated applicant with research experience in digital pathology, digital image analysis and advanced machine learning to take on a section lead within the Quantitative and Digital Pathology Group at University Hospital of Zurich. The successful applicant will lead their own research focus, will help to build research group capacity, engage in national and international collaborations and implement AI algorithms into diagnostic practice.

Your responsibility
  • Section lead of a digital pathology focus area.
  • Promote the development of digital pathology at Zurich University Hospitals
  • Participate in national and international collaborations involving academia and industry
  • Project-specific development of image analysis and machine learning algorithms for disease classification and patient stratification
  • Post-doc fellows with exceptional qualifications may be granted responsibility for co-supervising MSc, PhD, or MD students on a subject related to their research.
  • Scientific publications and presentations at national and international conferences are expected.

Arbeitsort:

8091Zürich

Please hand in your cover letter, your CV, certificates of your qualifications, your publication list and the contact details of two referees in a single pdf file. Please apply exclusively via the online application portal. Applications sent by e-mail or post will not be considered.