Position: Multidisciplinary Postdoctoral Candidate in Cancer Biology

Department: Division of Regulatory Genomics and Cancer Evolution / Division of Computational Genomics and Systems Genetics

Code number: 2022-0196

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 research groups of Prof. Dr. Oliver Stegle (https://www.dkfz.de/en/bioinformatik-genomik-systemgenetik) and Prof. Dr. Duncan Odom (https://www.dkfz.de/en/regulatorische-genomik) are seeking a postdoctoral fellow to join an ambitious collaborative project to decipher molecular networks by integrating AI-based analytics and causal inference with large-scale spatial transcriptomics analyses. 

Our research groups combine internationally leading excellence in experimental genomics technologies (Odom) with computational innovations in multi-omics integration, causal inference and machine learning (Stegle). The fellow will work in a highly multidisciplinary setting between both laboratories at the German Cancer Research Center (DKFZ) in Heidelberg. This project will generate novel insights into how clonal competition in three dimensions can shape tumour inception and cancer development in vivo.

Recent publications of the Stegle & Odom research groups:

  • Velten, Britta, et al. Identifying temporal and spatial patterns of variation from multi-modal data using MEFISTO. Nature Methods 19 (2022): 179-186.
  • Svensson, Valentine, Sarah A. Teichmann, and Oliver Stegle. SpatialDE: identification of spatially variable genes. Nature Methods 15.5 (2018): 343-346.
  • Argelaguet, R., et al. Multi-Omics factor analysis disentangles heterogeneity in blood cancer. Molecular Systems Biology 14.6 (2018): e8124.
  • S. Aitken, C. Anderson, et al. Pervasive lesion segregation shapes cancer genome evolution. Nature (2020) 265-270.
  • C Martinez-Jimenez†, N. Eling†, et al Aging increases cell-to-cell transcriptional variability upon immune stimulation. Science (2017) 1433-1436.


Job description:

    You will work in an integrated team of experimentalists and computational scientists to develop tailored machine learning and causal inference methodologies designed to fully exploit in vivo tumour data from spatial transcriptomics and single-cell multiomics analyses. We are especially looking for individuals with strong dual expertise in both experimental and computational analysis approaches. The two labs have established very dynamic framework for collaborative efforts. The specific project to be undertaken will be designed together with the successful candidate.


    The successful applicant will hold an academic degree (Master's and Ph.D.). This degree should be either in biological science with demonstrated experience in computational and statistical development or, conversely, in computer science, statistics, mathematics, physics, or engineering with a good understanding of corresponding biology.

    Previous experience in developing or the application of advanced analytical strategies to analyze large real world datasets is expected. Expertise in analysis of omics data, genetics, statistical interpretation and analysis of next-generation sequencing datasets is beneficial, as is communicating results in scientific conferences and papers. We are looking for a highly motivated, creative, organized, and well-positioned team member to lead this scientific project at all stages.


    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
    • Access to the DKFZ  International Postdoc 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 limited to 2 years with the possibility of prolongation.

    The position can in principle be part-time.

    Application deadline: 14.07.2022


    Dr. Duncan Odom
    Phone +49 (0)6221/42-3446

    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.