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.
Arc scaled to nearly 100 people in its first year. With $650M+ in committed funding and a state-of-the-art new lab facility in Palo Alto, Arc will continue to grow quickly to several hundred in the coming years.
About the position
We are looking for a Research Associate II to join the Zhou Laboratory at the Arc Institute. You will collaborate closely with Dr. Zhou, leveraging massive single-cell multi-omic atlas to solve human diseases. In this role, you will obtain training and experience to perform data analysis, deep learning algorithm development, and result interpretation for deriving novel biological insights. You will also have the opportunity to work with world-leading scientists in relevant fields, including computational genomics, human genetics, CRISPR technologies, and single-cell genomics. This is an excellent opportunity for a highly motivated and curious researcher interested in applying cutting-edge experimental and computational technologies to decode human diseases. This is also a good opportunity for candidates before enrolling in a Ph.D. program, as you will be involved in all stages of a project under the guidance of an experienced scientist and will receive a letter of recommendation.
This project builds on our unpublished data of single-cell DNA methylation and 3D genome structure across human tissues and also published single-cell RNA-seq and ATAC-seq data from other groups. This aims at developing a state-of-the-art computational framework to predict the effects of genetic variants on cell-type specific epigenome and transcriptome and combine them with human genetic frameworks to pinpoint disease-associated cell types and genes. The ideal candidate will have strong experience in deep learning and statistics and the motivation to learn and apply them to solve questions in genomics.
About you
- You love coding and biology. You are intrigued by making sense of massive biological data using AI technologies. You are also fascinated by a data-driven biological discovery that can be eventually validated by precise manipulation of our genomes.
- You are detail-oriented. You are careful and diligent about good documentation practices, good lab practices, and overall obsessed with keeping things organized.
- You love science and learning. Whether it’s gaining knowledge in new fields of scientific research or learning a new lab technique, you never stop being curious and routinely enjoy stepping out of your comfort zone to learn new things.
- You love to collaborate and help others. Science is a team effort and you pride yourself in taking the initiative to help.
- You are a problem solver. Science isn’t perfect and it’s common for you to come across issues you need to troubleshoot. You pride yourself in your ability to troubleshoot complex problems in the lab.
In this position, you will
- Perform data analysis for large-scale cross-tissue single-cell datasets, including sc/snRNA-seq, snATAC-seq, and snm3C-seq datasets
- Develop deep learning frameworks to predict functional effects of genetic variation on different regulatory modalities, and eventually elevate the fine-mapping of genetic risk loci for complex diseases
- Document your code, workflows, and protocols to ensure replicability and broad application in the community
- Present results in subgroup meetings, seminars, and conferences.
- Assist with research planning, execution, analysis, troubleshooting, and data interpretation with a high degree of independence and continued support from the rest of the team.
Job Requirements
- BS/MS or equivalent professional experience in bioinformatics, computer science, statistics, molecular biology, or another relevant field
- 2+ years of relevant experience (including independent lab work during your undergraduate studies) incorporating strong coding experience
- Proficient with machine learning and deep learning models and implementation, including model architectures such as CNNs and Transformers, as well as deep learning frameworks such as PyTorch
- Proficient coding in Python and Bash
- Experience or familiarity with genome-scale data analysis preferred, including some of the following: bulk and single-cell RNA-Seq, ATAC-seq, WGBS, Hi-C, and multi-omics integration
The base salary for this position is $73,700. This amount does not include benefits or other forms of compensation.
