Career Opportunities in the Biomedical Informatics Group
Our interdisciplinary research group develops and applies advanced methodology to mine large volumes of molecular and clinical data to understand and model mechanisms of molecular processes, diseases and treatment options.
Currently, this includes:
a) analyzing large cancer genomics data sets for new cancer-specific isoforms and mutations that influence RNA splicing,
b) developing methodology for summarizing electronic health records and model patient's health status,
c) performing association studies to connect molecular and clinical phenotypes with mutations.
The Biomedical Informatics Group welcomes applications for:
PostDoc in Machine Learning
We are seeking a highly motivated postdoctoral researcher with a strong machine learning background to join us in our vision to push the state-of-the-art in machine learning and subsequently address challenges arising in biomedicine. You will work on foundational machine learning challenges, leading projects, and collaborating with other researchers.
Doctoral student positions
We look for outstanding doctoral students from computer science and the life sciences. We accept direct applications and also participate in multiple graduate programs offered by the Life Science Zurich Graduate School of ETH Zürich and University of Zürich. We have exciting new projects on the boundaries of machine learning, medicine, and genomics. Come work in a team on projects that matter!
PostDoc in genomics
We are seeking a highly motivated postdoctoral researcher with a strong background in computational genomics and cancer genomics to join us in our endeavor to push the state-of-the-art in computational biology and address some of the major challenges arising in the integration and application of genomic data from cancer patients.
Software Engineer for scientific software development
We are looking for a highly motivated software engineer to: a) work with graduate students and postdocs in the group to develop scientific software (all open source), b) work with teams to develop and deploy clinically relevant software, c) establish software engineering best practices within the group, d) maintain software installations on a high performance compute cluster as well as web services and data resources in the lab.
For more information, please contact Gunnar Rätsch and use “#application #info” in the subject line. Please be patient while awaiting a response – we are a busy group!