Scientist I, Synthetic Biology
BioHubNew York, NY (Onsite)$120k – $150kPosted 18 April 2026
Tech Stack
Job Description
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.
The Team
The Biohub in New York 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. Biohub 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 Biohub facilitate research by scientists and clinicians at our home institutions and beyond
Diversity of thought, ideas, and perspectives are at the heart of Biohub 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 Biohub is seeking an accomplished Scientist I to lead innovative investigations into spatial architecture of molecular systems and its role in controlling cell state dynamics. In our newly established Synthetic Spatial Omics Laboratory, we advance next-generation spatial multi-omics platforms for understanding how cells process combinatorial signals, designing synthetic biology toolkits, and capturing cellular temporal histories with spatial resolution.
The successful candidate will lead independent research projects integrating spatial multi-omics, synthetic biology, and systems-level analysis to investigate molecular neighborhood reorganization in response to perturbations, engineer programmable cellular functions, and identify the molecular drivers of cell state transitions. This position offers the opportunity to drive both technology development and fundamental discovery in a highly collaborative, interdisciplinary research environment.
What You'll Do
Lead the development and application of imaging-based multi-omics technologies (e.g., seqFISH and related approaches) to map subcellular molecular organization and cell state transitions.
Design and perform perturbation experiments to decode how molecular neighborhoods respond to combinatorial signals.
Engineer synthetic biology systems and profile their behavior using spatial multi-omics to understand and program cellular functions.
Lead analysis of high-dimensional imaging and sequencing datasets using computational and machine learning approaches to identify organizational and regulatory principles.
Collaborate closely with researchers across genomics, synthetic biology, machine learning, and related disciplines.
Contribute to and lead preprints, publications, presentations, and open science practices.
What You'll Bring
Essential -
PhD in Systems Biology, Molecular Biology, Immunology, Bioengineering or a closely related discipline.
3-4+ years of postdoctoral or equivalent research experience, with a strong record of scientific productivity.
Demonstrated expertise in imaging-based omics and/or sequencing-based single-cell technologies.
Expertise in molecular biology ... (truncated, view full listing at source)
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