We are seeking a Senior Scientist to join the Discovery Research team as a Bioimage Scientist focused on tissue-based oncology diagnostics. This role sits at the interface of pathologists, biologists, and AI/ML teams, contributing directly to new assay development, DPAI tool development, biological interpretation, and diagnostic product advancement. This is a wet- and dry-lab role, responsible for developing, optimizing, and validating imaging assays and quantitative image analysis to link biological and clinical questions with interpretable image-derived metrics and features.

Location: San Diego (Hybrid)

Responsibilities

• Lead conception, design, execution and analysis of tissue-based imaging assays (including H&E, IHC, special tissue stains, multiplex stains, spatial biology).
• Build image analysis workflows to extract interpretable, multi-scale morpho-quantitative biomarkers.
• Design workflow controls, stress tests, quantification and scoring strategies to establish robust methods that connect biological/clinical hypotheses (e.g., immune contexture, tumor aggressiveness, treatment response) with explainable image-based measurements.
• Work closely with pathologists to define annotation schemas, perform and oversee WSI annotation to generate high-quality datasets for DPAI algorithm development, model interpretation, etc.
• Partner with bioinformatics and AI/ML teams to design, develop, test, and refine quantitative image analysis and DPAI workflows, from image QC and annotation strategies to biomarker quantification and explainability.
• Drive image-based tumor phenotyping and quantitative analyses to characterize tumor, stromal, and immune cell populations, interactions and features.
• Provide cross-functional technical leadership and mentoring in bioimage analysis, slide management and annotation, and TME characterization.
• Guide operational deployment of workflows and analytical tools, including automation, scaling, SOP and validation design for CLIA/CAP regulated environments.
• Evaluate, benchmark, and integrate, as appropriate, commercial and open-source image analysis tools and AI models that enhance diagnostic and research capabilities.

• An experienced bioimage scientist with deep hands-on expertise in tissue-based imaging assays, imaging analysis, quantitative histopathology and TME phenotyping.
• Familiarity with diagnostic product development.
• Comfortable operating at the interface of pathology, biology and AI/ML, translating complex tissue phenotypes into structured, quantitative data.
• Able to work with urgency and ownership in a fast-paced, cross-functional diagnostics environment.
• A clear communicator who can bridge pathologists, experimental scientists, and computational teams.

Requirements

• Ph.D. in biology, biomedical sciences, bioengineering, computational biology, or related field (oncology expertise preferred).
• 6 years postgraduate experience, with 3 years in regulated industry preferred.
• Proven expertise in tissue staining assays, IHC, imaging assay development, quantitative histopathology, bioimage quantification, slide annotation and TME phenotyping.
• Hands-on experience with image analysis platforms (ImageJ/FIJI, or similar), advanced quantification methods (Python, R, or similar), digital pathology annotation (QuPath, CaMic, Omero or similar) and analysis platforms (HALO, Visipharm, etc).
• Prior experience in developing digital pathology AI solutions, in immune-oncology biology, and TME characterization strongly desired.

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