Senior Principal Scientist / Assoc Director, Oncology Translational Research
Novartis
August 15, 2026
On-site
Cambridge, MA
Clinical Research and Development
Key Responsibilities
- Develop and deploy scalable workflows for whole-slide pathology image acquisition, processing, analysis, and interpretation.
- Apply AI/ML and quantitative image analysis to address biological, translational, and biomarker questions in human and preclinical samples.
- Provide expertise in digital pathology, spatial analytics, and AI-enabled biomarker quantification across oncology programs.
- Serve as subject matter expert for HALO/HALO AI and drive harmonization across Cambridge and Basel; build robust, reproducible, well-documented workflows.
- Build/optimize AI/ML models and reproducible pipelines for whole-slide, multiplexed, and high-plex tissue imaging; use HALO/HALO AI for segmentation, classification, feature extraction, spatial analysis, and biomarker scoring.
- Develop pipelines for RareCyte Orion (and other high-plex) data: process, analyze, visualize, interpret; define fit-for-purpose analytical approaches; establish QC, documentation, and reporting.
- Partner cross-functionally to design and interpret tissue-based studies; communicate strategies, recommendations, and findings to multidisciplinary teams.
Essential Requirements
- PhD or MS in biology, bioinformatics, biomedical engineering, computational biology, data science, pathology, or related field.
- Minimum 5 years industry experience.
- Significant experience in digital pathology and computational image analysis/imaging data science/translational oncology/tissue-based biomarkers.
- Expertise with HALO; experience developing/implementing/applying AI/ML models to tissue images.
- Proven success in pathology and translational workflows incl. high-resolution whole-slide/gigapixel datasets.
- Strong organizational, communication, and problem-solving skills; collaborative, self-directed.
Desirable Qualifications
- Cancer biology/immuno-oncology/radioligand therapy/spatial biology/tumor microenvironment.
- Experience with RareCyte Orion or other multiplexed/high-plex platforms; Python or R.
- Experience harmonizing digital pathology workflows; FAIR/enterprise platforms; collaboration with oncology data/informatics/enterprise AI teams.
Compensation (expected)
- Salary range: $138,600–$257,400 USD annually (performance incentive; equity eligibility depending on level).
- Develop and deploy scalable workflows for whole-slide pathology image acquisition, processing, analysis, and interpretation.
- Apply AI/ML and quantitative image analysis to address biological, translational, and biomarker questions in human and preclinical samples.
- Provide expertise in digital pathology, spatial analytics, and AI-enabled biomarker quantification across oncology programs.
- Serve as subject matter expert for HALO/HALO AI and drive harmonization across Cambridge and Basel; build robust, reproducible, well-documented workflows.
- Build/optimize AI/ML models and reproducible pipelines for whole-slide, multiplexed, and high-plex tissue imaging; use HALO/HALO AI for segmentation, classification, feature extraction, spatial analysis, and biomarker scoring.
- Develop pipelines for RareCyte Orion (and other high-plex) data: process, analyze, visualize, interpret; define fit-for-purpose analytical approaches; establish QC, documentation, and reporting.
- Partner cross-functionally to design and interpret tissue-based studies; communicate strategies, recommendations, and findings to multidisciplinary teams.
Essential Requirements
- PhD or MS in biology, bioinformatics, biomedical engineering, computational biology, data science, pathology, or related field.
- Minimum 5 years industry experience.
- Significant experience in digital pathology and computational image analysis/imaging data science/translational oncology/tissue-based biomarkers.
- Expertise with HALO; experience developing/implementing/applying AI/ML models to tissue images.
- Proven success in pathology and translational workflows incl. high-resolution whole-slide/gigapixel datasets.
- Strong organizational, communication, and problem-solving skills; collaborative, self-directed.
Desirable Qualifications
- Cancer biology/immuno-oncology/radioligand therapy/spatial biology/tumor microenvironment.
- Experience with RareCyte Orion or other multiplexed/high-plex platforms; Python or R.
- Experience harmonizing digital pathology workflows; FAIR/enterprise platforms; collaboration with oncology data/informatics/enterprise AI teams.
Compensation (expected)
- Salary range: $138,600–$257,400 USD annually (performance incentive; equity eligibility depending on level).