Job Description

Computational Biologist

A fast-paced biotech team is seeking a Computational Biologist to lead bioinformatics efforts in antibody discovery and engineering. This role is ideal for someone who thrives at the intersection of data science and molecular biology, and is excited to contribute to the development of novel biologics.

Key Responsibilities

• Analyze genomic and RNA-Seq datasets from public repositories to identify new therapeutic targets
• Oversee external efforts to verify gene sequences not yet available in public databases
• Lead development of intuitive databases housing antibody repertoire sequences
• Design and implement streamlined data entry workflows in Benchling for improved organization and accessibility
• Curate and integrate relevant genomic and transcriptomic datasets

Skills & Experience

• Deep understanding of machine learning approaches for protein design and biological data analysis
• Proven experience implementing bioinformatics tools for managing and analyzing large datasets (e.g., NGS, antibody libraries)
• Proficient in Python or R, with experience using libraries like Biopython and PyMOL
• Skilled in DNA and RNA sequencing data analysis
• Familiarity with molecular modeling tools such as Rosetta, Schrodinger, or MOE
• Strong background in antibody engineering, including liability remediation and biophysical optimization
• Excellent communicator and collaborator, comfortable in cross-functional teams
• Adaptable and effective in a fast-paced, small-team environment

Qualifications

• Ph.D. in Bioinformatics, Computational Biology, Statistics, or Biological Sciences with 3–5+ years of experience or
• MS in a relevant field with 10–15 years of experience and demonstrated expertise

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