Computational Biologist, Advanced Single Cell Technologies Platform (Biohub NY)

The Chan Zuckerberg Biohub New York (CZ Biohub NY) (https://www.czbiohub.org/ny/) is an independent nonprofit research institute that brings together three powerhouse universities - Columbia University, The Rockefeller University, and Yale University - into a single collaborative technology and discovery engine. CZ Biohub NY 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 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 organization where all colleagues feel inspired and know their work makes an important contribution.

The Opportunity

The Advanced Single Cell Technologies platform provides critical single cell profiling and perturbation assays, technology, and expertise to the CZ Biohub NY community. The goal of this platform is to use and develop cutting-edge single-cell technologies in collaborations related to studying human disease and the interaction of immune cells with human organs, which are foundational goals of the CZ Biohub NY. Our research focuses on scaling single-cell technology performance and incorporating diverse analytical dimensions (-omics) into unified single-cell platforms. The Computational Biologist should demonstrate strong familiarity with state-of-the-art single-cell analytical methods. We seek a candidate who excels at developing robust computational solutions, translating complex immunological data into meaningful biological insights, and working effectively across diverse research teams.

The Computational Biologist will possess deep expertise in current single-cell analytical frameworks, understand their inherent limitations, and demonstrate an ability to develop novel computational approaches as the field evolves. We seek candidates who share our excitement for the transformative potential of single-cell technologies.

What You'll Do

• Create new analytical pipelines and tools for emerging multiomic datasets
• Provide insight and direction for single-cell experiments relevant to studying the immune system
• Analyze CITE-seq/scRNAseq/scDNAseq/scATACseq datasets
• Mentor and train junior scientists in analyzing single-cell multiomic datasets
• Present research findings in academic journals and conferences
• Collaborate with other scientists to design experimental approaches and lead problem-solving initiatives

What You'll Bring

Essential –

• PhD degree in computational biology, systems biology, immunology, bioengineering, biology, or a related field
• At least four years of programming experience in Python
• Demonstrated experience developing computational tools for interpreting single-cell genomic information
• Expertise in bioinformatics including computational pipelines for analyzing bulk and single-cell genomic data (BWA, STAR, kallisto, scanpy, Seurat, etc.)
• Demonstrated engagement with the single-cell community (ex: hosting and maintaining single-cell tools)
  
• Ability to work efficiently in HPC environments
  
• Knowledge of immunology in a single-cell context, including analyzing CITE-seq datasets
  
• Familiarity with flow cytometry datasets
  
• Experience with containerization technologies (Docker, Singularity) for reproducible computational workflows
  
• Proficiency with version control systems (Git) and collaborative development p