is a venture-backed startup based in Cambridge, MA, composed of a small team of scientists and engineers pushing the boundaries of discovery at the intersection of computer science and biotechnology. Using our diverse backgrounds ranging from machine learning to genome engineering to protein biochemistry, we are building a platform to uncover and characterize nature’s inventions on an unprecedented scale to generate impactful applications in human health and sustainability.
We seek highly-motivated individuals with the dedication, integrity, and creative spirit needed to thrive in an innovative company. Working at Arbor offers a unique opportunity that combines the fast pace and growth opportunities of a startup with the intellectual rigor and creativity of academia. Our salaries are competitive, our benefits are generous, and our team is exceptional.
At Arbor, you will be at the cutting edge of biodiscovery, work with our computational and experimental teams to prototype and develop assays and methods to enhance and scale our discovery efforts. You will be expected to spearhead R&D development efforts, learn and adapt new techniques, and work efficiently within a small team. The ideal candidate will have a proven track record in execution and completion of diverse research projects, ability to rapidly iterate experiments, a strong desire to learn, and the self-motivation to be a key contributor within a tight-knit team.
- PhD or Masters in molecular/cellular biology, biochemistry, bioengineering, synthetic biology, systems biology, or a related field
- Developer or power user of library preparation for Next Generation Sequencing
- Demonstrated experience with diverse methods of cloning and mutagenesis
- Demonstrated ability across multiple projects to learn new techniques and technologies quickly and execute them towards high impact results
- Strong work ethic, motivation, and scientific curiosity
- At least 3 years of experimental research experience (industry or academic)
- Experience troubleshooting NGS library prep and preferred to have working knowledge or experience with NGS data analysis
- Experience using or developing high throughput genetic screening strategies either in vitro or in vivo
- Familiarity with scripting languages (Python, Bash, etc.) and previous computer science coursework