Scientist II, Bioinformatics/Computational Biology
Ikena Oncology is a clinical-stage biotechnology company that discovers and develops patient-directed, biomarker-driven therapies for cancer patients who need life-saving treatment, by understanding what drives their disease. Ikena is advancing five clinical, preclinical, and discovery programs. Ikena has entered into a global strategic collaboration with Bristol Myers Squibb and raised capital from top tier investors OrbiMed Advisors and Atlas Venture.
Ikena Oncology is seeking a highly creative, diversely experienced, and self-motivated bioinformatics/computational scientist to join an innovative, scientifically driven and fast paced team focused on developing breakthrough cancer therapies. This individual will be responsible for the computational aspects of drug discovery and development, working closely with discovery and translational scientists.
- Develop and maintain analytical and data visualization pipelines for next generation sequencing, imaging and pharmacological data
- Work in close collaboration with biology and translational teams to design and execute data analysis to support project needs
- Integrate and analyze multi-dimensional data from proprietary and publicly available datasets to support new target evaluation, biomarker discovery, indication selection and patient stratification
- Critically analyze results, detect relevant data associations, and prepare reports in form of presentations for the project teams
- Participate in the design, building and maintenance of databases to organize internal next generation sequencing data from the pre-clinical and biomarker data from clinical studies
- A Ph.D. in bioinformatics, computational biology or data science related fields with 2+ years of post-doc experience in academia or in the biotech/pharma
- Experienced in NGS and omic data analysis including RNA and DNAseq
- Deep knowledge of public genomic, transcriptomic databases and tools (e.g. TCGA, ICGC, cBioportal, DEMAP, IGV, ESEMBL)
- Experience with AWS environment preferred
- Experience with programming in R, Python or relevant language
- Good understanding of the genetic and molecular mechanisms of cancer
- Excellent data management and analytical skills. Ability to derive insights from complex multi-dimensional biological data including genomic, transcriptomic, single cell RNAseq, flow cytometry or IHC
- Deep experience applying statistics to the analysis of large datasets
- Demonstrated ability to multitask and excellent time management and presentation skills
Personal attributes: team oriented, goal-driven, organized, highly collaborative, open-minded, data-driven, creative, persistent in the face of obstacles and uncertainty, flexible, self-aware of strengths and weaknesses, objective in the evaluation of data and strongly optimistic about overcoming obstacles.