Computational Biologist Jobs

About The Position

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 Haves

• 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.

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.

Benefits

• Generous employer match on employee 401(k) contributions
• Paid time off to volunteer
• Funding for select family-forming benefits
• Relocation support