The LOOP Zurich is a medical center for translational research and precision medicine. It focuses on new approaches, better diagnostics, and novel therapies that will benefit patients and society as a whole. The goal is to enhance personalized healthcare by efficiently transferring scientific knowledge into medical practice.
As part of its strategy, The LOOP Zurich is developing an IT research platform (“LOOP BMIP Data Platform”) between the major Zurich hospitals and academic partners (University of Zurich and ETHZ) of strategic importance to the Zurich medical research ecosystem.
Summary The University of Zurich together with the University Hospital of Zurich are embarking on a concerted effort to develop informatics programs to advance biomedical research and healthcare using cutting edge computational approaches. As part of these efforts, the Chair of Medical Informatics (https://krauthammerlab.ch) investigates topics in clinical data science and translational bioinformatics, such as knowledge discovery from Big Data sources (Electronic Medical Records, health registries) as well as the analysis of human Omics data.
PhD in Biomedical Data Science and Bioinformatics We are looking for a PhD candidate to expand our multi-national research team of bioinformaticians and data scientists at the University of Zurich working on cutting-edge translational research problems. The main project that the candidate will be responsible for (and which provides funding for the position) concerns the multimodal data analysis in colorectal cancer (clinical records and multiomics).The candidate is expected to contribute to other on-going projects with regard to machine learning in genomics and bioinformatics.
We are currently looking for Master students interested to work on projects at the intersection of machine learning and medicine.
Machine-Learning for the Identification of Cost-effective Clinical Pathways Do you want to combine state-of-the-art machine learning (ML) algorithms with the pressing societal problem of high (and rising) healthcare costs? Are you motivated to work with interesting real-world data and excited to implement and apply machine learning algorithms?
High and rising healthcare costs are a significant challenge in many developed countries, which is expected to intensify with the demographic changes that will accelerate over the next decades.
We are currently looking for Master’s students in the field of Bioinformatics for the topic of
Nucleosome footprints in cell-free DNA sequencing data Cell-free DNA (cfDNA) is released by dying cells into the surrounding tissues and also to the bloodstream. As nucleosomes protect DNA from degradation, plasma cfDNA carries information about the nucleosome organization in the cells of origin. Different characteristics of cfDNA are increasingly being used in the diagnostics of genetic diseases and the monitoring of cancer.
We are currently looking for Master’s students in the field of Computer science, Statistics, or bioinformatics for the topic of
Developing generative models for structured data such as molecules, proteins, genetics, and graphs. Structured data are everywhere, text, sequences, graphs, molecules, proteins, genetics, and many others. Many real-world problem can be formulated as generating structured data. For instance, generating molecules with specific properties for drug design, and designing antibodies.
There has been a surge of research applying machine learning models for molecules, and protein design.
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.