The Chan Zuckerberg Biohub is looking for an energetic (data) scientist to work with us on understanding the evolution and spread of infectious disease.

This is a rare opportunity to use your state-of-the-art knowledge of evolution, phylogenetics, and genome assembly to have a direct impact on clinical medicine and global health.

Your first project might be to help us:

• Respond in real-time to diagnose and control hospital outbreaks by building accurate models of transmission and evolution.
• Understand the movement of mosquitos through California and (and eventually the world), together with the pathogens they carry.
• Develop a universal diagnostic for pathogen identification
• Build beautiful and useful tools to help clinicians and epidemiologists better respond to and understand outbreaks.

This is a permanent staff scientist position. The role will evolve as your career develops and the organization grows.

Vision

The Chan Zuckerberg Biohub is a new nonprofit biomedical research institute in San Francisco, California. We are a community of scientists and engineers with diverse backgrounds working together on some of the most urgent and challenging problems in cell biology and infectious disease. The Biohub has a unique structure: in addition to more traditional scientific research groups, there are five platforms: Bioengineering, Genome Engineering, Advanced Microscopy, Single-Cell Genomics, and Data Science. We are affiliated with UCSF, UC Berkeley, and Stanford.

The Data Science team works collaboratively with all the research groups at the Biohub, bringing our expertise in machine learning, mathematics, engineering, and statistics to their thorny biological problems. We also develop new algorithms, visualizations, and platforms, as the scale and complexity of data our wetlabs and collaborators produce often requires new approaches.

For example, we:

• Analyze gene expression in 100k’s of cells to understand aging.
• Design optimal CRISPR guides for identifying antibiotic resistance.
• Use deep learning to virtually stain images of cells
• Host workshops on machine learning and computing
• Create open source tools for the scientific community