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.
Are you an optimizer, automator, and tinkerer, not afraid to try out new processes, see what works best, and then share them with colleagues? Would you enjoy enhancing the productivity of Arbor’s scientists, computational and experimental alike? As the scientific operations associate, you will play this essential role in our discovery processes.
Your work will involve executing and automating routine tasks, such as reagent ordering and equipment upkeep. However, a key responsibility of your role will also be enhancement, not just maintenance. The ideal candidate will lead endeavors to increase the scale and efficiency of our scientific work, through the use of new hardware or software or by developing innovative new processes to actively nurture data flows between computational and experimental teams.
You’ll be supported by a great team of scientists, both computational and experimental, who take active ownership of developing and iterating best practices alongside you—we look forward to working together to push the boundaries of biodiscovery.
- BS or Masters in molecular/cellular biology, biochemistry, bioengineering, synthetic biology, systems biology, or a related field
- Demonstrated willingness to explore and innovate new tools, workflows, and organizational aspects
- Outstanding organizational and communication skills
- Quick learner and problem solver
- At least 1 year of experimental research experience (industry or academic)
- Ability to start as soon as possible
- Familiarity with scripting languages (Python, Bash, etc.)
- Liquid handling automation experience
- Minimum commitment of 2 years