The Hafner Group in Genentech’s Research and Early Development organization is looking for an exceptional Postdoctoral Fellow who will combine computational biology approaches with state-of-the-art deep learning methods to identify effective and selective drug combination treatments. The proposed project will be centered around modeling the mechanisms of action of targeted and chemo-therapies using high-content imaging data and expression data in order to predict the effects of drug combinations at scale.

The successful candidate will join a dynamic group and will develop an independent research project tackling challenging problems in cancer biology and leveraging the available resources. The project will benefit from a highly collaborative environment across the organization with opportunities to work closely with groups in cancer biology, high throughput imaging, and artificial intelligence.

You have a PhD in Computational Biology, Bioinformatics, Systems Biology, machine learning or related fields

You have a demonstrated record of innovative scientific accomplishments as evidenced by at least one first-author or co-first author key paper in a top journal

You have demonstrated the ability to apply machine learning methods for biologically meaningful interpretation of multiomics or imaging data.

You thrive working in a collaborative environment across departments

You have excellent communication and organizational skills

You are proficient in Python, R or other high-level programming languages and have experience in standard bioinformatics toolkits/programs

For more information about the postdoctoral program at Genentech please visit: http://www.gene.com/careers/academic-programs/postdocs

As a Senior Principal Scientist in gRED’s Oncology Bioinformatics at Genentech, Marc Hafner is managing computational biologists who collaborate with experimentalists in Discovery Oncology to identify new therapeutic targets, develop novel drugs, and find biomarkers of sensitivity. Marc's main interests are leveraging multimodal data to understand drug response and to study drug mechanisms of resistance with a focus on breast cancer. Before working at Genentech, Marc obtained his PhD from the Ecole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland and was a Swiss National Science Foundation Fellow in the laboratory of Prof. Sorger at Harvard Medical School (HMS) from 2012 to 2017.

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