Position: Postdoc in Machine Learning for Spatial Multi-omics of Glioblastoma

Department: Computational Genomics and Systems Genetics

Code number: 2022-0210

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 group of Prof. Dr. Oliver Stegle (Division of Computational Genomics and Systems Genetics, https://www.dkfz.de/en/bioinformatik-genomik-systemgenetik/) is looking for a highly motivated postdoctoral fellow to join an ambitious project to explore how the tumour microenvironment (TME) drives malignant cell states in glioblastoma (GBM) using large-scale spatial multi-omics. Funded as part of the Wellcome Leap program, the project "GBM-space" will bring together internationally leading experts to integrate single-cell transcriptomics, epigenomics and spatial RNA/DNA-sequencing to systematically deconstruct TME-GBM cell interactions and plasticity in situ.Our research group has a track record in the development of tailored computational methods for high-throughput omics data, machine learning for multi-omics integration and spatial omics.


Job description:

The successful candidate will lead the computational aims of the GBM-space project, which seeks to apply leading-edge spatial omics technologies to unravel disease-relevant signatures. A major opportunity within GBM-space is to develop novel analytical strategies and concepts for integrating spatial multi-omics datasets using leading-edge technologies. Ultimately, we hope to unravel genetic, epigentic and transcriptional intratumor heterogeneity in space and derive novel biomarkers for patient stratification and treatment recommendations.

You will be affiliated with the laboratory of Prof. Dr. Stegle, which is jointly located at DKFZ and EMBL Heidelberg and collaborate with the partners of the GBM-space project at the Wellcome Sanger Institute, Cambridge and the Crick. The position will also be connected to a vibrant local ecosystem for data science and machine learning, including the recently funded ELLIS Life Heidelberg unit. We seek to build on previous expertise and methods devised by our team (see below).

Recent publications of the Stegle research groups:

  • Kleshchevnikov, Vitalii, et al. Cell2location maps fine-grained cell types in spatial transcriptomics. Nature Biotechnology (2022): 1-11.
  • Velten, Britta, et al. Identifying temporal and spatial patterns of variation from multi-modal data using MEFISTO. Nature Methods (2022), 1-8.
  • 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.



The successful applicant will hold a doctoral degree or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological science with demonstrated experience in computational and statistical development.

We are looking for a range of talents and expertise, including theoretical foundations in probability, high-dimensional statistics, machine learning and Bayesian approaches. Expertise in biological data science and data-driven discovery, scientific programming and omics data analysis and genetics will be beneficial, as is communicating results in scientific conferences and papers. We seek 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 initially limited to 2 years with the possibility of prolongation. ‚Äč

The position can in principle be part-time.

Application deadline: 26.07.2022


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.