Associate Bioinformatics Scientist: Single-Cell Multi-Omics

The Chan Zuckerberg Biohub San Francisco (CZ Biohub SF) (https://(Use the "Apply for this Job" box below).) is an independent nonprofit research institute that brings together three powerhouse universities
- Stanford, UC Berkeley, and UC San Francisco - into a single collaborative technology and discovery engine. CZ Biohub SF itself supports some of the brightest, boldest engineers, data scientists, and biomedical researchers to investigate the fundamental mechanisms underlying disease and develop new technologies that will lead to actionable diagnostics and effective therapies. We are guided by our values of scholarly excellence;

disruptive innovation; hands-on engineering/hacking/building; partnership and collaboration; open communication and respect; inclusiveness; and opportunity for all.

Our Vision

• We pursue large scientific challenges that cannot be pursued in conventional environments
• We enable individual investigators to pursue their riskiest and most innovative ideas
• The technologies developed at CZ Biohub San Francisco facilitate research by scientists and clinicians at our home institutions and beyond

Diversity of thought, ideas, and perspectives are at the heart of CZ Biohub Network and enable disruptive innovation and scholarly excellence. We are committed to cultivating an inclusive organization where all colleagues feel inspired and know their work makes an important contribution.

The Opportunity

The Data Science platform at CZ Biohub SF (https://) is seeking an Associate Bioinformatics Scientist/Computational Biologist to join a fantastic team of computational biologists and data scientists. We develop computational methods, pipelines, and software that enable Biohub’s research across quantitative cell biology and infectious disease. In this position, you will closely collaborate with biologists and engineers from Biohub research groups such as the Royer group (https://)

and the Balla group (https://).

Potential projects include:

• Developing workflows to process and analyze single-cell multi-omics datasets (both in-house and publicly available datasets) to gain a holistic view of transcriptional regulation during zebrafish development
• Participating in data integration across multiple modalities (single-cell genomics, microscopy, etc.) to create a resource for the broader scientific community. Prime examples are our previous work, such as Zebrahub () and Open Cell ().
• Contributing to interactive web portals for in silico genetic perturbations on developing zebrafish at whole organism scale
  - Zebrahub v2.0 ().

This is an excellent opportunity to do both research and engineering at the intersection of bioinformatics, infectious diseases, and cell biology.

You will

• Contribute to scientific discovery via analysis of single-cell multi-omics datasets (transcriptomic, epigenomic, and/or proteomic)
• Participate in developing bioinformatics tools and web portals
• Optimize and execute data processing pipelines in an HPC environment
• Partner with biologists to conduct data mining and exploratory data analysis
• Author publications and disseminate research discoveries to the scientific community

You have

Essential –

• S. or M.S. degree in Data Science, Computational Biology, Bioinformatics, or a related discipline
• A minimum of 2 years of experience with scientific programming languages and data science workflows (e.g. Python, R, Git, UNIX command line, etc.)
• Familiarity with professional software development best practices (documentation, version control, etc.)
• Proven ability to implement exploratory data analysis and statistical inference in the context of scientific research
• A collaborative, team-focused mindset coupled with outstanding communication skills, and the ability to work in an agile environment

Nice to have -

• Experience with single-cell RNA-seq data analysis and/or other multi-dimensional omic data modalities
• Familiarity with the concepts of molecular biology, cell biology, genomics, and biostatistics
• Experience with high-performance computing (HPC) clusters and job…