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PostDoc in Machine Learning in Brain Imaging in Zürich

Studierende finden an der ETH Zürich ein Umfeld, das eigenständiges Denken fördert, Forschende ein Klima, das zu Spitzenleistungen inspiriert.


80%-100%, Zurich, temporary

The Bioimaging group of the Institute for Biomedical Engineering at the University of Zurich and ETH Zurich develops Magnetic Resonance technology and methods. UZH and ETH Zurich offer an international and world-leading research setting with first class infrastructure including the full range of clinical and experimental Magnetic Resonance systems as well as an excellent network of scientific and industrial partners.

Job description

The research position concerns application of advanced machine learning methods to improve detection and diagnosis of various brain diseases, in particular stroke, using large available databases of Magnetic Resonance (MR) and Computer Tomography (CT) images. In particular, the present work will focus on generating synthetic training data using variational auto-encoders (VAEs) and generative adversial networks (GANs).

Your profile

The candidate holds a first-class PhD degree in computer science, physics, mathematics, electrical engineering or biomedical engineering. He/she should present with excellent programming skills (Python / C(++) / Matlab) and interest in medical images analysis. An innovative spirit and team player skills round off the profile.

ETH Zurich
ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

We look forward to receiving your online application including a cover letter, a detailed CV and contact information of two referees. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

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