EMBL is seeking an expert in Computational Biology and IT to join Dr. Jan Korbel's group in the Genome Biology Unit. The position holder will actively participate in the design, development, and adjustment of interoperable workflows and pipelines to enable the analysis of data from the latest next-generation DNA sequencing platforms, including from single cell technologies. The post holder may get involved in analysing large numbers of human genomes, including from cancer patients and normal individuals of varying age to unravel the relationship of somatic mutations and ageing.
· Develop new computational workflows and analytical methods for human genome data analysis
· Design and implement cloud-based workflows for single-cell sequencing protocols, particularly Strand-Seq
· Integrate tools in pipelines and workflows and optimize their interoperability, efficiency, usability and portability
· Participate in cutting-edge research projects of the Korbel group by helping with data analysis and data management tasks
· Interact with other scientists at EMBL and partner networks (Elixir, de.NBI) in an international, interdisciplinary, and highly collaborative work environment
· A M.Sc. or PhD in Computational Biology, Bioinformatics, Physics or Computer Science with a background in large-scale genomics data handling
· Advanced programming skills in at least one high level programming language (Java, C, or C++), R Statistics and one scripting language (Python, Julia)
· A solid knowledge in database technologies (SQL), cloud computing frameworks (OpenStack, GNOS), containerization technologies (Singularity, Docker), code version control (git) and continuous integration services (CI)
· A strong interest in computational data analysis and data management
· Strong communication skills as well as the ability to interact with other scientists and to work in an international and interdisciplinary team
· A basic understanding of molecular genetics and cancer research
What else you need to know
The Korbel group at the European Molecular Biology Laboratory (EMBL) combines experimental and computational approaches – including single-cell sequencing technology, genome sequencing, big data analytics, and machine learning – to unravel determinants and consequences of germline and somatic genetic variation. Our group is using bulk as well as single cell-based omics approaches for investigating mechanisms behind complex phenotypes in humans, ranging from common diseases including cancer to ageing. An over-arching theme centers on the formation and selection of germline and somatic genetic variation in health and disease states, in particular genomic structural variation (SV).