PhD Position in Computational Biology in Heidelberg bei Deutsches Krebsforschungszentrum

Job description:

The project covers two main aspects. One aspect focuses on developing computational methods and workflows to answer clinically relevant questions across the range of childhood cancers by interrogating genomic and epi-genomic alterations. We aim to elucidate the mechanisms underlying cancer predisposition, tumorigenesis and therapeutic response to discover novel therapeutic targets and to improve diagnosis, prevention and clinical outcome in children (Autry group).

The second focus lies on clinical drug screening, identification of novel biomarkers in both patient and/or cell line data and the overall integration of multi-omics data with drug sensitivity profiling. These duties include development and maintenance of a cohort-based drug response classification application and script writing for automated drug screening workflows. The group is also interested in high-content imaging thus it would be advantageous if the applicant had some basic knowledge in AI-based image analyses (Oehme group).

This is an exciting opportunity for a computationally minded student to learn and develop computational approaches to discover novel therapeutic strategies leading to immediate clinical translation. We are seeking an enthusiastic researcher who wants to work at the precipice of research and translation and is motivated to apply their knowledge towards improving pediatric cancer treatment and outcomes

Your tasks:

• Performing genomic analyses on cancer predisposition patients and identifying novel predisposition genes on several ongoing studies directed at cancer predisposition
• Developing and maintaining drug screening pipelines and visualization methods

Requirements:

• Applicants must hold a master's degree (or equivalent) in bioinformatics, computational biology, genomics and biostatistics, computer science or a related subject.
• Bioinformatics analytical skills and experience with Linux / Unix command line and programming languages (e.g., Python, R, and Bash) are expected as well as the willingness to expand existing knowledge.
• Experience in working in machine learning and high-performance computing environments is beneficial.
• Expertise in the analysis and integration of next-generation sequencing and other multi-omics data is a plus.
• Excellent communication skills and the ability to write publications, present research proposals and results and represent the lab at meetings and conferences.
• Excellent interpersonal skills and the ability to work independently as well as part of a team.