Position: Bioinformatician / Computational Biologist

Department: Computational Genomics & Systems Genetics

Code number: 2022-0274

The German Cancer Research Center is the largest biomedical research institution in Germany. With more than 3,000 employees, we operate an extensive scientific program in the field of cancer research.

The German Human Genome-Phenome Archive (GHGA, www.ghga.de) is part of the national program for research data infrastructures (NFDI). As a node of the federated European Genome-Phenome Archive, GHGA will contribute towards the establishment of an international infrastructure for human genome data. These activities are closely coordinated with leading international initiatives and networks, such as the Global Alliance for Genomics and Health (GA4GH). This infrastructure will support genomics data hubs with software tools for secure data / metadata storage, interactive data portals with data visualization, and streamlined data deposition and acquisition solutions. The GHGA main office, which is coordinated by Prof. Oliver Stegle (Division of Computational Genomics and Systems Genetics), is located at DKFZ in close coordination with the European Molecular Biology Laboratory (EMBL, Prof. Jan Korbel).


Job description:

We are looking for a bioinformatician or computational biologist to implement and maintain data processing and analysis workflows as part of GHGA. As part of the role, you will take responsibility to implement, optimize and extend existing data processing frameworks such as NextFlow to meet the demands of large-scale genome data processing. We seek to establish a system that comprehensively addresses all steps of omics data processing, ranging from data quality control to variant calling and downstream analysis and integration. The successful candidate will be part of an interdisciplinary research and data management team developing and applying a diverse range of state-of-the-art methodology to implement and maintain bioinformatics workflows in a cloud compute environment. The role will involve close cooperation with other partners in the GHGA network, as well as international networks and initiatives.

Your tasks:

  • Development of a standardized workflow framework using cloud environments 
  • Workflow development and maintenance for NGS data processing and analysis for canonical tasks, including:
    • Read Alignment 
    • Somatic and germline variant calling (SNV, Indel, SV, CNV, …) 
    • Data integration and visualization 
  • Containerization of existing workflows 
  • Improvement of bioinformatics workflows with respect to performance and stability
  • Testing / benchmarking workflows with cloud deployments
  • Development of cloud images for (human) bioinformatics 

We offer the opportunity to help shape one of the most important emerging scientific data infrastructures for the storage and exchange of omics data in Germany.

Your possibilities: 

  • Get exposed to a plethora of fields ranging from AI-guided clinical decision making to modern web development technologies 
  • Work with an interdisciplinary team of experts bringing state-of-the-art biomedical research closer to clinics and patients 
  • Take part in international organizations such as the Global Alliance for Genomics and Health (GA4GH), the European Genome-Phenome Archive (EGA) and ELIXIR shaping the future of genomics across borders 
  • Widen your expertise with extensive possibilities of training programs, seminars and conferences 



  • PhD in computer science, mathematics, physics, bioinformatics, computational biology or similar background with focus on bioinformatics or data science; alternatively a MSc or equivalent qualification with complementary years of relevant experience 
  • Hands-on experience with workflow development and genomics data analysis using open source software and algorithms, using workflow languages (WDL, CWL, Nextflow) 
  • >2 years of experience with software containerization tools like Docker, Singularity 
  • Proficiency with UNIX-based systems and relevant programming languages such as Python or R  is a prerequisite 
  • Expertise in software development and cloud computing is beneficial

The ideal applicant should have demonstrated the ability to work independently and creatively. The candidate should have excellent communications skills in English and be able to articulate clearly the technical needs, set clear goals and work within an interdisciplinary setting, communicating with other partners.

    We offer:

    • Interesting, versatile workplace
    • International, attractive working environment
    • Campus with modern state-of-the-art infrastructure
    • Salary according to TV-L including social benefits
    • Possibility to work part-time
    • Flexible working hours
    • Comprehensive further training program

    Important notice:

    The DKFZ is subject to the regulations of the Infection Protection Act (IfSG). As a consequence, only persons who present proof of immunity against measles as well as against COVID-19 may work at the DKFZ.

    Earliest Possible Start Date: as soon as possible

    Duration: The position is initially limited to 2 years with the possibility of prolongation.

    The position can in principle be part-time.

    Application Deadline: 23.08.2022


    Prof. Dr. Oliver Stegle
    Phone +49 (0)6221/42-3598

    Please note that we do not accept applications submitted via email.

    The DKFZ is committed to increase the proportion of women in all areas and positions in which women are underrepresented. Qualified female applicants are therefore particularly encouraged to apply.

    Among candidates of equal aptitude and qualifications, a person with disabilities will be given preference.

    To apply for a position please use our online application portal (https://www.dkfz.de/en/stellenangebote/index.php).

    We ask for your understanding that we cannot return application documents that are sent to us by post (Deutsches Krebsforschungszentrum, Personalabteilung, Im Neuenheimer Feld 280, 69120 Heidelberg) and that we do not accept applications submitted via email. We apologize for any inconvenience this may cause.