
Scientist Computational Biology (Biologics)
- Boston, MA
- $111,800-175,670 per year
- Permanent
- Full-time
- Develop and implement robust pipelines for analyzing large-scale bulk and single B-cell sequencing datasets for biologics discovery workflows, including QC, annotation, prioritization, and reporting of heavy and light chain/VHH sequences.
- Improve antibody screening and in silico analysis workflows by implementing standard automated protocols for the antibody curation, annotation, and interpretation of large antibody-specific datasets
- Lead the biologics discovery campaigns using well-designed, and optimized bioinformatics workflows to accelerate therapeutic discovery by analyzing sequencing datasets from various sources, such as immunization and selection campaigns.
- Propose a rationale library design strategy based on the antibody selection output to further affinity mature and optimize biologics.
- Advance antibody sequences from in vitro (yeast and phage), in vivo (single/bulk B cells/VHH) or de novo (AI-based) platforms with the goal to deeply interrogate repertoires, expand functional sequence diversit,y and affinity to accelerate the lead discovery.
- Collaborate with cross-functional teams to integrate sequencing data with other data generated from antibody discovery engine
- Ability to use AWS and HCP infrastructure for additional compute needs
- Use Docker and GitHub for reproducibility of workflow and version control, respectively
- Develop UI to seamlessly integrate flow of sequencing data from various discovery platforms and relevant information
- Meet established timelines, maintain accurate records of work, and present data at team, departmental, and company-wide meetings
- Education: BS, MS, or PhD in a relevant scientific field
- Experience: If BS, then 11+ years. If MS, then 9+ years. If PhD, then 2-3 years of previous work experience
- A strong background in computational biology and scientific programming languages (R/Python)
- In-depth experience analyzing NGS data, including B-cell receptor and antibody repertoire sequencing data and selection data from antibody surface display
- Deep overall understanding of in vivo and in vitro antibody discovery platforms
- Minimum 2 years of industry experience in hands-on NGS data analysis (RNAseq /scRNAseq) utilizing custom workflows and pipelines.
- Demonstrated ability to write, test, automate, and benchmark computational pipeline tools with a focus towards biologics discovery.
- Experience with AI/ML and deep learning-based methodology is a plus.