We are looking for Masters Students!

We are currently looking for Master’s students in the field of Computer science, Statistics, or bioinformatics for the topic of

Developing Machine Learning Models for Drug Synergy Prediction

Drug synergy is a phenomenon where the combined effect of two drugs is greater than the sum of their individual effects. While a vast amount of data exists for single drug effects on cell lines, there is a scarcity of data for drug synergy due to the huge number of possible drug combinations. Therefore, there is growing interest in employing computational methods to predict drug synergy for untested drug pairs. Our project focuses on the development of machine learning models, including graph neural networks, to forecast the synergy between any two drugs when applied to a specific cell line.

We are searching for committed Master’s students who share a genuine passion for exploring Deep Learning models and their practical applications in forecasting drug synergies. Our ideal candidates should possess a fundamental understanding of machine learning concepts, statistics, and linear algebra. Proficiency in Python coding, coupled with experience in PyTorch libraries, is a prerequisite.

For a comprehensive overview of the project, please consult the following research paper You can apply by sending a CV to this e-mail along with a short description of your motivation to join our lab.

For CBB master students at ETH, please check this form .

For other students at ETH: you need be enrolled at UZH as a mobility student, see here . If you have any questions regarding ETH regulation, please contact the Student Exchange Office: Dr. Francesca Broggi-Wüthrich, francesca.broggi@akd.ethz.ch, Tel +41 44 632 43 46.

Michael Krauthammer

Interested in (a) moving data-driven solutions into patient care and (b) knowledge discovery from big biomedical data sources