Senior Scientist, Protein Engineering

Flagship Pioneering, Inc.•Cambridge, MA

3d•$126,000 - $181,500

About The Position

Flagship Labs 129 (FL129) is an early-stage biotechnology startup with an ambitious and exciting mission: to unlock the future of small molecule drug discovery. FL129 is developing a revolutionary approach to this challenge and is recruiting a team of top-tier scientists to build this powerful and first-in-category platform. This is a unique opportunity to be one of the first employees of a biotech startup that combines an innovative mindset with the resources and know-how of Flagship Pioneering. This is a hands-on role with substantial ownership for a scientist who is excited to set technical direction from day one and, over time, help build the team. We are seeking a motivated and highly collaborative Senior Scientist to join FL129’s growing team of experimental and computational scientists to build a novel platform technology. The successful candidate will have a strong track record of scientific and technical innovation in the design, construction, and functional interrogation of large protein variant libraries, including deep mutational scanning and related library-scale methods. Deep experience with protein display systems, high-throughput sorting, and sequencing-based readouts is essential, and familiarity with bioinformatic analysis of variant-level data is strongly desired. The ideal teammate will be highly adaptable, have strong organizational and communication skills, and will thrive in a highly collaborative and multidisciplinary environment.

Requirements

Ph.D. in molecular biology, biochemistry, protein engineering, or a similar field with 5+ years of industry or postdoctoral experience.
End-to-end experience with deep mutational scanning or related library-scale mutagenesis methods, from variant library design and construction through selection, sequencing, and variant-level data analysis.
Hands-on expertise in library-scale molecular cloning, including site-saturation or degenerate-codon mutagenesis, high-efficiency transformation, and managing library complexity, variant coverage, and bottlenecking.
Experience with protein display systems that link genotype to phenotype, such as yeast surface display (YSD), mammalian display, or phage display.
Experience with fluorescence-activated cell sorting (FACS), including selection strategy and sort-gate design for quantitative variant enrichment.
Experience with next-generation sequencing (NGS) technologies (Illumina and PacBio), including amplicon sequencing and long-read approaches for variant–barcode linkage, and ideally single-cell sequencing technologies.
Experience with protein expression and purification, and with biochemical/biophysical assay development to quality-control library inputs and quantitate the bioactivity of library outputs.
Motivated team-player and independent force-of-nature with strong organizational and written/verbal communication skills.

Nice To Haves

experience with machine learning methods for protein engineering, or with statistical analysis of variant fitness landscapes.
entrepreneurial spirit, strong communication skills, and comfort in working in and contributing to a dynamic and cross-functional team environment.

Responsibilities

Technology development, aligned with FL129’s core strategic goals. This role is among the first hires, and we’re looking for someone who thinks critically and will influence the company’s scientific direction.
Design, construction, and experimental testing of large-scale protein variant libraries, including deep mutational scanning and related saturation mutagenesis approaches
Establish and optimize display, selection, and sorting workflows that link protein genotype to measured phenotype
Assess library quality and variant coverage, and validate library outputs by biochemical and biophysical characterization of purified proteins
Optimize existing workflows and establish best experimental and documentation practices to enable platform excellence.
Ensuring rapid and accurate turnaround of data to drive achievement of key project goals.
Translate experimental data into meaningful insights and present results at team meetings.