Computational Scientist 3 (Spatial Omics & Computational Pathology)

TL;DR

Computational Scientist 3 (Spatial Omics & Computational Pathology): Developing AI pipelines and models for spatial omics and digital pathology with an accent on computer vision, representation learning, and multi-modal data integration. Focus on architecting scalable imaging infrastructure and embedding biological priors into generative AI models to uncover spatial niches and cell-cell interactions.

Location: South San Francisco or Pleasanton, CA, USA. Relocation benefits are available.

Salary: $129,200 - $240,000

Company

hirify.global, a member of the Roche group, is a biotechnology pioneer dedicated to discovering and developing groundbreaking medicines for serious and life-threatening diseases.

What you will do

• Serve as the Technical Lead for computer vision, AI/ML, and multiplex imaging projects, architecting pipelines for whole-slide images and spatial omics data.
• Design and implement cutting-edge ML algorithms, including foundation models and generative architectures for image segmentation and predictive modeling.
• Develop multi-modal representation learning frameworks to fuse morphological features with molecular data (transcriptomics/proteomics).
• Engineer scalable imaging data infrastructure using OME-ZARR, OME-TIFF, and SpatialData on HPC and cloud environments.
• Embed biological priors, such as metabolic pathways or spatial knowledge graphs, into the mathematical design of AI models.
• Collaborate with pathologists and researchers to interpret data, visualize results, and contribute to experimental design.

Requirements

• Ph.D. in Computational Biology, Computer Science, ML, Imaging Science, Data Science, or a related field (or Masters with 3+ years of experience).
• Demonstrated experience in computer vision, deep learning, or image processing specifically with tissue-based or high-dimensional imaging data.
• Strong foundation in digital pathology workflows and advanced machine learning (probabilistic, representation, and generative modeling).
• Deep proficiency in Python and extensive experience with frameworks like PyTorch, TensorFlow, or JAX.
• Experience applying ML to single-cell spatial transcriptomics and proteomics (e.g., 10X Genomics Xenium, Visium, Lunaphore COMET).
• Must be based in or be able to relocate to the USA.

Nice to have

• Familiarity with the scverse ecosystem (Scanpy, Squidpy, SpatialData, scVI) and libraries like OpenCV and scikit-image.
• Solid understanding of tissue histology, cell biology, and tumor microenvironments.
• Experience developing agentic AI systems, LLM-driven autonomous workflows, or advanced AI tools for biological datasets.

Culture & Benefits

• Competitive compensation with a discretionary annual performance bonus.
• Relocation benefits available for this position.
• Comprehensive benefits package provided by a member of the Roche group.
• Work environment at a company recognized on the Fortune 100 Best Companies to Work For list for over 24 years.