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Department of Quantitative Biomedicine

Open Positions

Master Student Position in the Kümmerli lab

16.04.2024

Bacteria use a wide range of structures and compounds to compete with each other for ecological niches. These competitive mechanisms are either contact independent such as the release of diffusible toxins or contact dependent requiring cell-to-cell contact between the attacker and the receiver. An example of this contact-dependent inhibition is the Type 6 Secretion System (T6SS). The T6SS works as a molecular spear gun that punctures the cell wall of the adversary and thereby injects poisonous effectors into the target cell. The molecular apparatus of T6SS has been extensively studied in well-characterized laboratory strains of Vibrio cholerae or Pseudomonas aeruginosa. However, relatively little is known about the abundance of T6SS and its use among bacteria in natural communities. In this master thesis, you will focus on a collection of natural Pseudomonas bacteria isolated from soil and pond habitats (at Irchel campus). You will screen the isolates for the presence of the T6SS, their capacity to use it to kill a common prey (Escherichia coli), and the ability of environmental strains to use T6SS to outcompete other community members. You will learn several key methods and skills such as the design of high-throughput screening experiments, fluorescent microscopy and flow cytometry to quantify the efficiency of the T6SS in direct competition, and the statistical and graphical analysis of data in the R environment. Moreover, this project could also involve bioinformatic genome analysis depending on time and interest.
This Master project takes part at the UZH Irchel campus. Interested applicants can write to: simon.marechal@uzh.ch for more information.

Starting date: Summer 2024 or upon arrangement.

Duration: 12 months

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PhD Students in the Joller lab

05.04.2022

PhD students interested in joining the Joller lab are exclusively recruited through the Microbiology and Immunology program of the Life Science Zurich Graduate School.

Application deadlines are July 1st and December 1st every year.

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Master Students and Medical Students in the Joller lab

Flexible starting date

We regularly have openings for motivated UZH and ETH students with a strong interest in immunology. To discuss possible projects, please send your CV and a few sentences on why you would like to join our lab to Nicole Joller.

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Computational Master Student Projects in the Krauthammer lab

Flexible starting date

The Krauthammer lab is currently looking for Master’s students in the field of Bioinformatics for the following topics:

1. Analyzing cell-free DNA fragmentation patterns in clinical samples

This project aims to improve diagnosis and prognosis through liquid biopsies in cancer and various other diseases. Cell-free DNA (cfDNA) carries information on the epigenetics of distal tissues and organs. We discern epigenetic signatures from cfDNA-sequencing data and connect those to diagnoses and patient outcomes. The student should have basic experience with Unix systems, some experience with at least one scripting language (e.g. Python or R), a strong understanding of biostatistics and a basic understanding of machine learning algorithms. Depending on the experience and interest of the student we offer projects focusing on either:

  • Feature extraction from cfDNA-sequencing data using bioinformatic tools and comparison to nucleosome coverage or methylation data or
  • Representation learning from high-dimensional cfDNA-sequencing data

2. Data integration in Cancer Genomics

The project’s aim is to characterize the effects of transcriptional and epigenetic processes on mutational patterns in cancer. The student should have basic experience with Unix systems and some experience with at least one scripting language (e.g. Python or R). Prior experience with genomics software and data formats is an advantage.


The Krauthammer lab is currently looking for Master’s students in Clinical Data Science for the following topics:

3. Information extraction from German Radiology Report

Large, labeled datasets have driven deep learning methods to achieve expert-level performance on a variety of medical imaging tasks. There are some English radiology report datasets that have been labeled automatically to detect in presence of 14 observations by capturing uncertainties inherent in radiograph interpretation. We would like to investigate different approaches such as the information extraction paradigm to label radiology reports in another language such as German. We plan to explore the possibility of incorporating domain knowledge such as http://radlex.org/ and evaluate the effectiveness of it in the proposed framework. Since a radiology report comes with radiology images, we also would like to investigate the multi-modal approaches in our study.

4. Trait prediction using Big data and machine learning

Genome-wide association studies rely on big cohorts of hundreds of thousands of participants with gene sequences amounting to TB of information. This project is interested in predicting relevant traits like disease risk and identifying this risk’s genetic component. We also are interested in resolving possible confounders in this kind of data, like pairwise interactions.

The model and data reading are already implemented, objectives of a short project would be to:

  • Accelerate data reading and training
  • Perform experiments on performance and hyperparameter tuning.
  • Select the best performing predictor and test in an external cohort.

The student should have experience with Unix Systems, good experience with Python and ML frameworks (preferably TF 2). Additional experience with quantitative genetic tools like plink would be advantageous.

Applications can be done by sending a CV to this e-mail along with a short description of the student’s motivation to join our lab.

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Master Student positions in the Bodenmiller lab

Flexible starting date

The Bodenmiller lab is seeking to fill several Master Student positions, with flexible starting date. These projects are in the field of

  • Quantitative biology I: Simultaneous analysis of up to 100 markers in tumors using a new technology, called imaging mass cytometry [Link]
  • Quantitative biology II: Analysis of how tumor cells become metastatic
  • Computational biology: Computational analysis of signaling networks

Please send your CV and a few sentences why you would like to join our lab to Bernd Bodenmiller

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Weiterführende Informationen

Life Science Zurich Graduate School

Life Science Zurich Graduate School

Next LSZGS application deadline: 1 July 2023

BSc-, MSc & PhD Theses

BSc-, MSc- and PhD students are welcome to write their thesis at the DQBM. Please contact the group leader of your choice to ask about opportunities.