Post-doctoral researcher

Development of interpretable AI methods for computational biology

Ref. 2020_031

Project description

A postdoctoral research position is available at the IBM Research Laboratory in Zurich to develop AI-driven models focused on the early detection of cancer. Many cancers, e.g. pancreatic cancer, are very difficult to detect at early stages, where tumors are still treatable. As patients do not experience any symptoms, cancer diagnosis occurs at a late stage, which significantly reduces the probability of cure, while increasing the complexity and side-effects associated with the treatment.

This project will focus on the analysis and modelling of genomic and molecular data from cancer patients, with a special focus on breast and pancreatic cancer. The work will revolve around the development of new AI approaches to facilitate early detection. A focal point of the project will be the application and/or development of new methods based on Interpretable Artificial Intelligence, with the goal of not only detecting new cancer cases with high accuracy, but also identifying highly predictive molecular markers that can pinpoint the oncogenic mechanisms behind cancer onset.


The successful candidate will work in a highly interdisciplinary team and be supported by the rich AI community assembled at lab in Zurich. Candidates should have a strong background in computer science, mathematics or physics and be interested in cancer-related research. Strong programming skills are necessary. Experience in mathematical modelling, statistics, probability and machine learning and/or deep learning are especially welcome.

About the group

The systems biology group at IBM aims to develop new mathematical and computational approaches for the analysis and exploitation of the latest generation of biomedical data. In the context of cancer, the group focuses on the development of computational and statistical approaches to unravel cancer molecular mechanisms using high-throughput multi-omics datasets and single-cell molecular data. A major interest is the development of artificial intelligence approaches for personalized medicine and drug modelling, activities that have been supported by two H2020 consortia: PrECISE (2015-2018) and iPC (2019-2022).


ZRLIBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent flexible working arrangements enable all genders to strike the desired balance between their professional development and their personal lives.

How to apply

Interested candidates please submit an application consisting of a CV, list of publications and at least 2 letters of reference.


Questions? Contact Dr. María Rodríguez Martínez,