Scientist, Molecular Engineering

The Arc Institute is a new scientific institution conducting curiosity-driven basic science and technology development to understand and treat complex human diseases. Headquartered in Palo Alto, California, Arc is an independent research organization founded on the belief that many important research programs will be enabled by new institutional models. Arc operates in partnership with Stanford University, UCSF, and UC Berkeley.

While the prevailing university research model has yielded many tremendous successes, we believe in the importance of institutional experimentation as a way to make progress. These include:

• Funding:
  Arc fully funds Core Investigators’ (PIs’) research groups, liberating scientists from the typical constraints of project-based external grants.
• Technology:
  Biomedical research has become increasingly dependent on complex tooling. Arc Technology Centers develop, optimize, and deploy rapidly advancing experimental and computational technologies in collaboration with Core Investigators.
• Support:
  Arc aims to provide first-class support—operationally, financially, and scientifically—that will enable scientists to pursue long-term high risk, high reward research that can meaningfully advance progress in disease cures, including neurodegeneration, cancer, and immune dysfunction.
• Culture:
  We believe that culture matters enormously in science and that excellence is difficult to sustain. We aim to create a culture that is focused on scientific curiosity, a deep commitment to truth, broad ambition, and selfless collaboration.

Arc has scaled to nearly 300 people. With $650M+ in committed funding and a state of the art new lab facility in Palo Alto, Arc will continue to grow quickly in the coming years.

We are seeking a highly skilled and motivated Scientist with a strong background in cellular engineering and stem cell biology to join the Molecular Engineering team within the Genome Engineering Technology Center at the Arc Institute. In this role, you will design, generate, and characterize engineered human pluripotent stem cell (hPSC) lines for arrayed genetic perturbation screens in complex organoid models used to recapitulate and probe human genetics of neurodegenerative disorders.

Examples of engineering projects include developing optimized effector systems for gene knockdown and activation that function robustly throughout differentiation, introducing rare coding variants to model disease-associated mutations, and implementing novel genome engineering technologies to expand perturbation capabilities. Through this work, you will play a critical role in the Institute's Alzheimer’s Disease Initiative, an ambitious cross‑functional effort aimed at identifying and drugging rational therapeutic targets to combat devastating neurodegenerative disorders.

This position is highly collaborative and the candidate will have a unique opportunity to interface with pioneering labs that have developed the fundamental toolbox for genome engineering and functional genomics screens, such as CRISPR nucleases, CRISPRi, CRISPRoff, CRISPRa, and serine or bridge recombinases.

• You are passionate about science and excited about answering questions related to molecular design, genome engineering technology development, and complex human diseases.
• You embrace challenges and often formulate creative solutions to develop new approaches and optimize existing tools to answer complex biological questions.
• You understand the importance of collaboration and thrive when working with a diverse team of scientists.
• You have a deep commitment to data quality while working in a fast‑paced environment.
• Your organizational skills enable you to manage multiple concurrent projects, and your curiosity and creativity drive you to continuous learning and innovation.

• Develop and optimize engineered hPSC lines for arrayed genetic perturbation screens in complex organoid models, applying genome engineering strategies tailored to the desired edit and experimental goals.
• Design and implement systematic approaches to identify, benchmark, and optimize effector systems for gene knockdown and…