The Role: BigHat Biosciences is seeking a self-motivated individual for a Senior Research Associate or Associate Scientist* to contribute to and support research on multiple therapeutic antibody engineering/optimization projects.
*At BigHat we believe in titles that are commensurate with skill set, relative organizational impact, and value contribution; more experienced candidates are encouraged to apply, with the understanding that responsibilities and title would adjust as appropriate.
- Plan and execute experiments to discover antibodies or to optimize antibody expression, purity, stability, developability, binding affinity, and/or functional activity.
- Contribute to the development and optimization of new assays to be run in high-throughput, using automated liquid handlers.
- Create SOPs for new or modified assays that demonstrate superior antibody function and transfer SOPs to the Production team as appropriate
- Follow laboratory protocols and keep a detailed record of all experiments using BigHat’s documentation tools.
- Communicate progress and challenges regularly to ensure efficient progress towards Program goals.
- Analyze & summarize results and critical problems in writing and in presentation to a collaborative, cross-functional team.
About you:
- MS or PhD in the biological sciences or engineering; familiarity with protein biochemistry/biophysics or protein engineering; strongly self-motivated individual with attention to detail; driven, team-oriented, and excited to work in a dynamic startup environment.
Nice to haves:
- MS or PhD in biochemistry, bioengineering, structural biology, or related field
- Hands-on knowledge of protein expression and purification
- Experience with mammalian cell culture
- Experience with ELISA/immunoassay, BLI/SPR, other protein biochemical/biophysical characterization, and/or cell-based assays
- Exposure to protein engineering and high-throughput screening
- Familiarity with (or interest in) operating automated liquid handlers
- Ability to process, analyze, and visualize data in R/Python (or similar)