We are continually inviting applications for postdoc, PhD and internship positions. You can apply for one of two tracks:
- Method development in statistical computing and bioinformatics,
- Biological discovery through integrative data analysis (“dry biology”)
For track 1, you will have strong quantitative and analytical skills, such as acquired through a degree in mathematics, statistics, physics, computer science or a related field. You have curiosity and motivation to work in interdisciplinary projects, which include generation of new data and their analysis, and are eager to get to grips with relevant areas of biology and the technologies used in biology research. You will have experience in scientific computing and be familiar with one or several computer languages. Familiarity with R is definitively a plus.
For track 2, you will have a training in life sciences and strong coding skills that enable you to undertake complex data transformations, integrative operations, applications of mathematical models and visualizations. You are driven by making fundamental discoveries by mining cutting-edge, large data sets.
To apply, please contact Wolfgang with your CV, a brief statement of research interests, and examples of your work: besides your publications, this can include theses, research reports, talk slides, software projects (e.g. R packages, github projects) or data analysis reports (e.g. markdown reports or Jupyter notebooks).
Here are some keywords and a non-exhaustive list of collaboration partners with whom we work frequently on new, exciting data types:
- Latent spaces and manifolds estimation from multi-modal single cell data
- Genotype-drug interactions, precision oncology, multivariate biomarker discovery
- Imaging-based phenotyping
- Thorsten Zenz – pharmacogenomics of drug response in blood cancer
- Sascha Dietrich – systems medicine of cancer drugs
- Lars Steinmetz – systems genetics & ‘omics technology development
- Michael Boutros – high-throughput genetics, genetic interactions & synthetic lethality in cancer
- Henrik Kaessmann – evolution of cell types