Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere.
Our immune cell reprogramming team integrates foundational research on immunology and disease biology with AI-modeling to develop engineered cells that harness our own immune system to detect and treat early signs of age-related diseases, like cancer, Alzheimer’s, and Parkinson’s. These technologies will enable precise, context-dependent therapeutic responses only when and where it is needed. You can learn more about our work here.
Our work brings together three powerhouse universities - Columbia University, The Rockefeller University, and Yale University - into a single collaborative technology and discovery engine.
Our Vision
We are a team of passionate individuals powered by technology, guided by scientific research, and driven by collaboration, working toward a mission to cure or prevent all disease.
The newly established Laboratory of Synthetic Spatial Omics at CZ Biohub NY (https://takeilab.org/) advances our understanding of engineered immune cell function within their native microenvironment to design better cell therapeutic approaches. Toward this goal, we develop and integrate state-of-the-art immune cell engineering, imaging-based and sequencing-based multi-omics, and machine learning/AI frameworks. We bring together scientists with diverse expertise to pursue highly interdisciplinary scientific challenges.
We are seeking a creative and highly collaborative Computational Biologist to develop and apply computational methods for imaging-based multi-omics datasets generated in the laboratory. The primary focus of this position will be to uncover interpretable relationships among molecular state, cellular morphology, subcellular organization, engineered design, and tissue context in endogenous and engineered immune cells. The successful candidate will work closely with experimental scientists to shape studies, design analytical strategies, and drive projects from experimental planning through biological interpretation and publication. This position offers the opportunity to develop novel computational frameworks at the intersection of spatial omics, synthetic biology, immunology, and machine learning.
Interested candidates should submit the following documents:
Please note that the target start date for this role is January 2027.
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The New York City, NY base pay range for a new hire in this role is $153,000.00 - $191,000.00. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.
This position may be eligible to participate in our discretionary annual performance bonus program. Bonus eligibility and targets are determined in accordance with our total rewards philosophy and may vary by role.
As we grow, we’re excited to strengthen in-person connections and cultivate a collaborative, team-oriented environment. This role is a hybrid position requiring you to be onsite for at least 60% of the working month, approximately 3 days a week, with specific in-office days determined by the team’s manager. The exact schedule will be at the hiring manager's discretion and communicated during the interview process.
We’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible.
If you’re interested in a role but your previous experience doesn’t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.
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