Reference number: 2024-0383

Heidelberg
Full-time
Precision Sarcoma 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 Precision Sarcoma Research Group is seeking for the next possible date a

Our group is seeking a computational biologist to join the efforts of the consortium “DECIPHER-M: Deciphering Metastasis with Multimodal Artificial Intelligence Foundation Models” (Coordinators: Daniel Truhn, RWTH Aachen; Jakob Niklas Kather, EKFZ Digital Health & TU Dresden). This 5-year consortium will be initiated at the beginning of 2025 and is funded by the German Federal Ministry of Education and Research (BMBF) under “Major unanswered questions in cancer research” in the framework of the National Decade against Cancer.

YOUR TASKS

The candidate will focus on the establishment and execution of single-cell and spatial omics analysis workflows, followed by the application of these data to deconvolute mechanistic processes from artificial intelligence-based composite signatures derived from foundation models, which in turn, are generated from multimodal clinical and molecular profiles of patients with metastatic cancer. The successful candidate will lead this project within a multidisciplinary team of molecular biologists and clinicians, overseeing the design, execution, and coordination of research activities as well as scientific communication.

YOUR PROFILE

• PhD or equivalent in bioinformatics, computational biology, cancer biology or similar
• Strong background in analyzing and integrating large-scale bulk multi-omics datasets, experience in single-cell and spatial-omics approaches
• Proficiency in programming languages such as R and Python, bash scripting and deep learning frameworks
• Ability to acquire and process data from sequencing facilities or public resources, work with HPCs, run, adapt existing pipelines (in-house or nf-core) and develop new ones
• Strong publication record, including lead authorships, with experience in collaborative research and supervision of students or interns
• Comprehensive knowledge of cancer biology and cancer genomics, maintained through rigorous literature review and applied to data interpretation and project advancement
• Demonstrated ability to work both independently and collaboratively, with high self-initiative, a strong work ethic, and team-oriented mindset

Applications must include a CV, cover letter, complete list of publications, references or recommendation letters, and expected availability date. Incomplete applications will not be considered.

WE OFFER

ARE YOU INTERESTED?

Then become part of the DKFZ and join us in contributing to a life without cancer!