Senior Scientist I
Library Design and Construction
Updated on 11/15/2023
Generate Biomedicines

51-200 employees

Utilizes machine learning for biological engineering to create
Company Overview
Generate:Biomedicines is a unique therapeutics company that combines machine learning, biological engineering, and medicine to create groundbreaking medicines. Their Generate Platform broadens the scope of technical possibilities, altering the traditional methods of medicine production. This intersection of technology and biology positions them as a leader in the industry, offering a competitive edge through their unique approach to creating therapeutics.
AI & Machine Learning

Company Stage

Series C

Total Funding





Somerville, Massachusetts

Growth & Insights

6 month growth


1 year growth


2 year growth

Cambridge, MA, USA
Experience Level
AI & Machine Learning
  • Ph.D. in Microbiology, Molecular Biology, Bioengineering, Biochemistry, Biophysics or related field with at least 4+ years of post degree related experience; industry experience preferred.
  • Strong hands-on experience in designing and creating large scale libraries (defined, combinatorial, DMS, etc.)
  • Extensive experience with multi-part DNA assembly cloning techniques (Golden Gate, Gibson Assembly, in vivo recombination, etc.) and DMS library creation techniques (nicking mutagenesis, PFunkel, etc.)
  • Experience developing and implementing pooled high throughput assays (bacterial directed evolution, pooled CRISPR screen, AAV screening, displayed antibody selections, etc.)
  • Experience generating and interpreting NGS data (Illumina, nanopore, PacBio) in the context of pooled assays
  • Strong analytical skills for troubleshooting experiments
  • Excellent collaboration skills and ability to work cross-functionally and balance multiple projects in a dynamic environment
  • Excellent presentation and written communication skills
  • Work with bioinformatics team to translate machine learning hypotheses into libraries of testable proteins and automate the design of defined and combinatorial libraries
  • Drive the build of such libraries, including design of vectors, inserts, and cloning methodologies
  • Develop novel construction methods for massive-sized libraries
  • Actively engage with protein engineering, platform innovation, NGS and data sciences teams to determine library build and NGS strategies for developing large scale quantitative assays to generate data for machine learning models
  • Provide intellectual and technical expertise on other synthetic biology related workflows and tech dev projects, such as vector design, gene assembly etc.
Desired Qualifications
  • Display technology (phage, yeast, bacterial, ribosomal, mammalian, etc.) experience
  • Bioinformatic skillset for analyzing NGS data
  • Experience with microfluidics for ultrahigh-throughput reactions
  • Lab automation experience