We are looking for a statistician or data scientist to run the Centre for Statistical Data Analysis, which is affiliated with the research group of Wolfgang Huber and with the EMBL Bio-IT team, which provides support on computing, data management and bioinformatics to scientists across EMBL.
- Provide statistical consulting on biological data analysis for EMBL researchers conducting cutting-edge molecular biology research
- Advise and help researchers with their experimental design, data analysis and interpretation of results
- Provide training (2-5 days courses) in the area of computational statistics and data science in biology
- Collaborate and interact with other scientists at EMBL and partner networks (Elixir, de.NBI) in an international, interdisciplinary, and highly collaborative work environment
The consultancy engagements typically range all the way from brief high-level methodological advice to in-depth collaborations and solving novel statistical challenges emerging from new research data, methods and technologies. The emphasis of the position is on providing excellent service, in addition, it offers opportunities to make own research contributions.
- A PhD or equivalent qualification in a quantitative science (statistics, mathematics, computer science, physics, bioinformatics) with solid theoretical foundations in probability and applied statistics
- Programming skills in R
- Strong interest in computational statistics
- Motivation to teach and provide advice
- Good communication skills in written and spoken English and ability to interact with other scientists in interdisciplinary teams
- Basic experience in analysis of high-throughput biological data (genomics, transcriptomics, epigenetics, proteomics, etc.)
- An interest in cutting-edge molecular biology and its data-generating technologies
Why join us
EMBL has a large thriving community of bioinformaticians, working in close collaboration with experimental scientists and with strong links to other local scientists and institutions. The position also offers the opportunity to help shape future developments of ‘data science’ in biology, such as publication and communication best practices.
For more information and to submit your application, please visit our website. Closing date: 29 September.