Postdoctoral Fellow – Bioinformatics job with EMBL

The Steinmetz group at EMBL Heidelberg is looking for an ambitious computational fellow (postdoc or research scientist, depending on the level of experience) interested in developing novel computational tools to explore exciting large-scale sequencing datasets of different cellular modalities and biological applications. We offer unique opportunities to develop own ideas using a multitude of data types that are generated in our lab on a daily basis. Our interest focusses but is not limited to the following areas:

• integrating data from different of single-cell modalities (genomes, transcriptomes, phenotypes) to understand the genetic basis of complex diseases

• explore long-read sequencing of genomes and transcriptomes of synthetic organisms and develop computational tools to understand the structure and evolution of genomes

• developing novel tools to analyze long-read and short-read sequencing data with isoform specificity of complex in vitro and in vivo disease model systems

• analyzing data from large-scale Perturb-seq/TAP-seq datasets by developing novel computational tools for causal inference and by leveraging the power of AI/ML

Our lab works across model organisms and systems, including yeast, human cells, complex 3D cell culture models, and animal models. We also work with synthetic organisms, such as the world’s first fully-synthetic eukaryote, Saccharomyces cerevisiae 2.0, which features an on-demand genome-wide recombination system engineered into its genome, to discover principles of genome design within an evolutionary context. Our lab has both wet lab and computational scientists, and works in long-standing collaborations with leading computational labs, such as Wolfgang Huber and Oliver Stegle.

 

Your role

• Lead the computational work in a team including one or several experienced experimental postdocs or PhD students

• Work in close collaboration with experimental scientists

• Process and analyse data from high-throughput sequencing experiments

• Develop, publish and maintain bioinformatic software

• Keep abreast of the latest methods in omics data generation, integration, and analysis • Develop computational tools for novel experimental techniques and technologies with academic and industrial partners

• Present ongoing work and findings internally and at conferences

 

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