We are seeking a talented and motivated Computational Biologist to join our expanding Data Sciences team. You will tackle challenging bioinformatics and computational biology problems to advance our understanding of Gene Writing and help accelerate programs to the clinic. You will contribute scientific, technical, and leadership expertise to a multidisciplinary team, emphasizing conceptualization, experimentation, data analysis, presentation, and strategic planning. Key Responsibilities:
- Work both independently and as part of a collaborative, multi-disciplinary team to design, analyze, and interpret multi-omics technologies focused on understanding gene writing systems.
- Lead the Implementation of computational pipelines to develop and understand novel and existing NGS-based technologies to identify on-target and off-target gene writing events.
- Process, analyze, and interpret data from a wide variety of research and preclinical projects to develop rigorous hypotheses.
- Lead and mentor junior scientists to collectively achieve team goals.
- Collaborate closely with experimental scientists to ensure that data is effectively utilized for high level impact.
- Present scientific findings to broad audiences including senior leadership to drive decision making in program teams
- Ph.D. (or comparable experience) in Computational Biology, Bioinformatics, or related quantitative discipline.
- 6+ years of industry experience in discovery research.
- Proficient with experimental design, data processing, statistical analysis, and bioinformatics analysis/reporting of next-generation sequencing data.
- Fluency in one or more programming languages with bioinformatics applications (R, Python).
- Track record of success working in a fast-paced, cross-functional, and rapidly growing organization.
- Outstanding written and verbal communication skills, ability to work with colleagues from diverse scientific backgrounds and cultures.
- Experience with recent advances in gene therapy and development of gene editing platforms as therapeutics.
- Familiarity with computational methods for understanding molecular results of gene editing outcomes including on-target, off-target, and structural variants.
- Familiarity with short and long read next-generation sequencing platforms (Illumina, PacBio, Nanopore).
- Proficiency in handling large scale sequencing data in a cloud environment (AWS preferred).
- Proficiency in statistics and machine learning.