Computational Biologist, Synthetic Spatial Omics

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.

About the Team

The 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.

The 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. 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.

About the Role

The team is 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.

Target start date for this role is January 2027.

Responsibilities

• Lead the computational analysis of multiplexed imaging, spatial omics, and other high-dimensional datasets generated from endogenous and engineered immune cells.
• Develop novel computational and machine-learning approaches to identify interpretable biological, organizational, and regulatory principles from cellular morphology, molecular state, subcellular organization, and spatial context.
• Build models that predict molecular states, functional outcomes, or perturbation responses from imaging and multimodal measurements.
• Work closely with experimental scientists to design studies, define controls, establish quantitative benchmarks, and iteratively improve experimental and computational workflows.
• Develop robust, reproducible, and scalable analysis pipelines and software.
• Depending on expertise, contribute to the computational design or evaluation of synthetic receptors, transcription factors, protein circuits, and other programmable molecular components.
• Contribute to preprints, publications, presentations, and open science practices.

Requirements

• PhD in Computational Biology, Computer Science, Biomedical Engineering, or a closely related discipline.
• Minimum 2 years of experience in developing AI/ML-based computational frameworks.
• Strong programming skills in Python, R, or a comparable scientific computing environment.
• Strong track record of research productivity, including publications, and close collaboration with experimental scientists.
• Solid foundation in cell biology and genomics.
• Ability to independently design rigorous computational frameworks, troubleshoot complex workflows, and drive projects to completion.
• Collaborative mindset and strong scientific communication skills.

Nice to Have

• Evidence of methodological creativity through the development of computational methods, software, or novel analytical frameworks.
• Experience analyzing multiplexed microscopy, tissue imaging, or imaging-based spatial omics data.
• Experience with cell segmentation, representation learning, spatial statistics, morphological profiling, or subcellular image analysis.
• Experience analyzing single-cell, perturbation, or multimodal omics datasets.
• Experience with computational protein design, de novo receptor design, transcriptional regulation, or synthetic protein circuits.
• Familiarity with immunology, engineered immune cells, or synthetic biology.

Pay

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.

Schedule

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.

Benefits

• Generous employer match on employee 401(k) contributions to support planning for the future.
• Paid time off to volunteer at an organization of your choice.
• Funding for select family-forming benefits.
• Relocation support for employees who need assistance moving.