Postdoctoral Training Fellow – Bioinformatician
A position of a Bioinformatician, at the level of Postdoctoral Scientist, has been created to carry out research on the immunological impact of endogenous retroviruses in the development and progression of cancer, using large-scale genomics and transcriptomics data.
This role will be pivotal in ensuring continuation of research on immunity to exogenous and endogenous retroviruses and cancer in the Kassiotis lab. The post holder will be part of a team of researchers in the Kassiotis lab at the Francis Crick Institute.
Lab web page: https://www.crick.ac.uk/george-kassiotis
These include but are not limited to;
- Working within a team that carries out research on immune reactivity to retroviral antigens in the context of infection and cancer.
- Carrying out the processing, analysis and integration of distinct next generation sequencing and multiple ‘omics data.
- Using existing, and developing and maintaining pipelines for the analysis of multiple ‘omics data.
KEY EXPERIENCE AND COMPETENCIES
The post holder should embody and demonstrate our core Crick values: bold, imaginative, open, dynamic and collegial, in addition to the following.
- PhD in computational biology, computer science, or biology
- A strong background in statistical analyses
- Experience in the analysis of next generation sequencing data
- Experience with scripting language (Python or Perl), R statistical programming language, Bioconductor, and with LINUX based systems
- Ability to design and maintain analysis pipelines
- The post holder is expected to be creative and motivated, conscientious and able to work independently, but also to interact well within the team
- Excellent record keeping and ability to communicate well in English are also essential
- Demonstration of scientific ability and excellence by means of authorship (first author) peer reviewed publications in internationally recognized scientific journals
- Experience in bioinformatics analysis of repetitive elements
- Experience in bioinformatics analysis of T cell receptor repertoires