Postdoc Position in Computational Cancer Biology (ERC funded)

at  Deutsches Krebsforschungszentrum

“RESEARCH FOR A LIFE WITHOUT CANCER” IS OUR MISSION AT THE GERMAN CANCER RESEARCH CENTER. WE INVESTIGATE HOW CANCER DEVELOPS, IDENTIFY CANCER RISK FACTORS AND LOOK FOR NEW CANCER PREVENTION STRATEGIES. WE DEVELOP NEW METHODS WITH WHICH TUMORS CAN BE DIAGNOSED MORE PRECISELY AND CANCER PATIENTS CAN BE TREATED MORE SUCCESSFULLY. EVERY CONTRIBUTION COUNTS – WHETHER IN RESEARCH, ADMINISTRATION OR INFRASTRUCTURE. THIS IS WHAT MAKES OUR DAILY WORK SO MEANINGFUL AND EXCITING.

In collaboration with European Molecular Biology Laboratory (EMBL) in Heidelberg, the Junior Research Group “Genome Instability in Tumors” headed by Dr. Aurélie Ernst is offering a
We are looking for a postdoctoral scientist (bioinformatics / computational biology) to work on chromosome instability in space and time and understand the early stages of cancer development, using data from single-cell multiome and spatial profiling in the brain and the colon. The project is funded through the ERC “Unstable Genome”.
The position is co-supervised by Wolfgang Huber at EMBL and Dr. Aurélie Ernst at DKFZ.
The Huber group develops statistical and machine learning methods for modern biotechnologies, applies them to biological discovery, and translates them into reusable tools (https://www.huber.embl.de/)
The Ernst group aims at elucidating how chromosome instability leads to massive genome rearrangements and deciphering implications for cancer patients.
More information can be found at https://www.dkfz.de/en/genominstabilitaet-in-tumoren/index.php.

YOUR TASKS

As part of the research team, you will participate in the overall project and shape your own research profile in one or several of the following areas:

• Integrative data analysis for biological discovery
• Single-cell multiome data analysis at ultra-large scale (>100 000 cells per donor)
• Spatial transcriptomics
• Clonal evolution and phylogeny
• Copy-number changes and complex rearrangements and their impact on the transcriptome at single-cell resolution
• Clone fitness and selection, interactions between tumor cells and the microenvironment
• Data science, quality assurance, advanced visualization and model checking
• Develop scalable and robust software for scientific computing.

You will be able to contribute both to scientific discovery by analysis of primary data, and to the development of more broadly usable computational methods and tools.