About Arc Institute
The Arc Institute is a new scientific institution that conducts 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 will fully fund Core Investigator’s (PI’s) 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.
With $650M in committed funding, the vision in the first 2-3 years is to grow from 60 people to a team of roughly 200 team members, with plans for further significant growth over the decade ahead.
About the position
The Konermann lab at the Arc Institute is looking to hire a Computational Scientist to lead our efforts in discovering new Genome Engineering tools. Critically, the close proximity of wet lab and computational scientists in the lab enables a tight feedback loop between computational analysis and experimental design and execution for model refinement. This role will also play a crucial part in building and maintaining systems for high-utility data and software dissemination. Long relegated to the back burner in academic biomedical science, we believe that an investment into biological software development will address a major gap in modern research.
Examples of computational work from the lab include: Transcriptome Engineering with RNA-Targeting Type VI-D CRISPR Effectors and Deep learning and CRISPR-Cas13d ortholog discovery for optimized RNA targeting
We are flexible for this position to be in person, hybrid or remote (with the need to visit Arc’s headquarters 1-2 days per month).
In this position you will
- Apply computational creativity to develop new analyses such as developing next generation transcriptome engineering tools via new discovery and ML based engineering
- Work as part of a fully funded team to conduct experiments involving high-throughput functional genomics in human cell lines and primary cells, molecular and cellular assays, and iPSC-based models of disease
- Independently lead key research projects and provide guidance on project strategy, experimental design, data analysis, and troubleshooting
- Collaborate with and mentor PhD students and Research Associates
- Masters (or equivalent) in computational biology, computational chemistry, computer science, chemical engineering, bioengineering or a related field
- General experience with wide range of next generation sequencing and omics data sets and flexibility to analyze different types of data
- Knowledge of modern machine learning technologies (deep neural networks, language models, transformers, etc.)
- Experience programming in Python, bash, and/or R
- Experience with cloud computing (i.e. AWS) and software is a plus
- Thrive in a collaborative environment involving different stakeholders and subject matter experts
- Strong communication, data presentation and visualization skills