Other Location: Los Angeles, CA
We are seeking an independent and motivated Computational Biologist to join our Computational Immunology group. You will work on an interdisciplinary team to develop new computational tools to study the tumor-immune microenvironment and analyze data from our growing collections of genomic data coupled with clinical data. The successful candidate will work in an interdisciplinary team, carry out data analysis, and apply and develop best-in class algorithms that directly address important biological and clinical questions.
What You’ll Do:
- Design and develop new computational tools and assays for our clinical genomics platform to improve patient care.
- Work with software engineers and product designers to bring those tools into our production pipeline.
- Analyze the world’s largest collection of clinical and molecular data from cancer patients to identify new scientific insights.
- Share those insights with the greater scientific and medical community through publication.
- Ph.D. in a relevant quantitative discipline (e.g. statistics, bioinformatics, computational biology, genomics, or computer science) or a Ph.D. in cancer biology, immunology, or molecular biology combined with significant previous experience with high-throughput sequencing data analysis. M.S. in a quantitative discipline with significant relevant experience will be considered.
- Must have significant previous experience working with next generation sequencing data, including whole exome sequencing, RNA sequencing, and/or TCR/BCR sequencing.
- Fluent in python and preferably R.
- Interest in Immunology and Immunotherapy.
- Significant quantitative training in machine learning or statistics.
- Previous experience working in diagnostic technologies, human immunology, or cancer biology.
- Experience writing, maintaining, or contributing to high-quality, reproducible, collaborative code.
- Experience with cloud computing, containerization, high-performance computing.
- Self-driven, capable of independent work and collaborating effectively in a team.