We are seeking innovative, collaborative and accomplished computational biologists/data scientists to work on a variety of genomics projects in the field of immuno-oncology and autoimmune-diseases. This position will work on multiple internal and external datasets composed primarily of single cell RNAseq data. A critical component of the job will be to develop and implement innovative analysis strategies to generate focused hypotheses for the identification of new therapeutic targets.
Successful candidates will join a dynamic and growing team of scientists using cutting edge genomics techniques and single cell sequencing for the discovery of new targets. Primary responsibilities will be to:
- Generate meaningful biological hypotheses from genomics data.
- Prioritize and validate drug discovery targets.
- Apply or develop new tools or data-mining techniques for integrative analysis and visualization of large data-sets.
- Develop a platform for genomics-based target discovery.
- Contribute to experimental study design.
- A Ph.D. in Bioinformatics, Computer Science, Biology, Genetics or equivalent, and a minimum of 5 years of experience in computational biology and genomics required.
- A strong background in cancer biology and/or single cell genomics and/or immunology.
- Strong scientific background and publication record with proven high levels of performance.
- Ability to innovate, apply and develop new tools for the integrative analysis and visualization of multi-dimensional genomics datasets.
- Experience with machine learning algorithms and data mining methods.
- Familiarity with pathway analysis.
- Proficiency with R, Python or other scripting language for statistical computing and graphics.
- Experience with cloud computing is a plus.
- Ability to adapt to increasing scope and complexity of work brought on by growth/change and helps others manage through change.
- Strong written, oral and public speaking communication skills.
- Knowledge of industry trends and ability to utilize that knowledge to determine the most efficient ways to meet business needs.