Role Overview
As a Senior Computational Biologist you will be a crucial part of our Research & Development team. This role will involve conducting and interpreting biological discoveries from Nomaly, our proprietary AI technology for genomics analysis. You will also apply standard data analyses and bioinformatics tools alongside scientific literature, to support the identification and understanding of the arising biological targets and disease mechanisms.
Key Responsibilities
- Use and improve research tools for a variety of diseases and the investigation of genes, DNA elements, proteins and pathways identified by our AI genomics technology, mainly by
- Deployment & running of Nomaly and other software in research environments (UK Biobank, Genomics England, etc)
- Deployment & running of Nomaly and other software on AWS, Google cloud & Azure
- Analysis and data mining of Nomaly output and results
- Cross-referencing and integration with other datasets
- Collaborate with a multidisciplinary team of scientists and researchers
- Keep the company’s software and products up-to-date with the latest developments in genomics and biomedical informatics
- Take responsibility for company projects in this area
Qualifications
Requirements
- A background of high performance in computational biology, and/or molecular/cell and disease biology
- A PhD or equivalent industry experience, either in Bioinformatics/Computational Biology, or in Computer Science with strong knowledge of biology
- Demonstrable experience of responsibility for management and delivery of projects
- Well-developed programming skills, particularly in languages commonly used in bioinformatics such as Python or R
- Good communication and teamwork skills
Desirables
- Strong analytical and problem-solving skills
- Experience of biological research in molecular/cell biology of disease
- Proven track record of publishing high-impact scientific papers in a related field, or in delivering and completing projects or building bioinformatics tools and resources
- Practical experience of relevant bioinformatics tools and use of online databases
- Linux environment and some systems administration
- Pipelines, cloud computing environments or HPC
- Genomics experience, e.g. GWAS, cohorts, etc.