Postdoc in Machine Learning & Non-invasive Tumor Profiling

at  Deutsches Krebsforschungszentrum

Reference number: 2024-0299

Heidelberg

Full-time

Clinical Cooperation Unit “Multiparametric Methods for Early Detection of Prostate Cancer” and Division „Cancer Genome Research”

“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.

The research departments of Prof. Dr. Holger Sültmann (Cancer Genome Research) and PD Dr. Magdalena Görtz (Multiparametric Methods for Early Detection of Prostate Cancer) have joined forces to advance novel multi-omics profiling technologies using liquid biopsy samples to improve treatment decisions in solid tumors. Our aim is to develop diagnostic panels for non-invasive diagnosis and monitoring of tumor diseases.
The two department are jointly seeking from January 2025 a

YOUR TASKS

We are looking for an excellent bioinformatician / computational scientist to lead our efforts in multimodal tumor profiling. The core of this role is the development of integrative analysis approaches to establish disease-relevant signatures using NGS data from liquid biomaterials. You will be responsible for applying these methods to large datasets and combining data from liquid biopsies, clinical information, and imaging. Your tasks will also include the processing as well as the integration of these modalities into harmonized data structures.
You will be jointly affiliated with the laboratories of Prof. Sültmann and PD Görtz and will collaborate with partners at the DKFZ, the University Hospital of Heidelberg, as well as national and international collaborators.