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# AI Scientist - Image Analysis & Digital Pathology

- **Company:** Novartis Corporation
- **Location:** Cambridge, MA, United States
- **Experience:** Experienced
- **Salary:** $126,000.0 - $234,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computational Biology, Computer Programming, Image Analysis, Machine Learning, Pytorch, Deep Learning, Generative AI, Information Technology, Data Analytics, Feature Extraction
- **Published:** July 30, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=478aa4bd95b85b15

## About the Role

* Ph.D. in Machine Learning, Computer Science, Applied Mathematics, Computational Biology or related field. Candidates with MSc in Machine Learning, Computer Science, Applied Mathematics, Computational Biology or related field, with 4+ years of relevant industry experience will also be considered.
 * Strong experience analyzing pathology imaging modalities including H&E, IHC, multiplex IF, and / or spatial transcriptomics data.
 * Understanding of machine learning methods for segmentation, classification, detection, and representation learning.
 * Experience in one or more of the following areas: generative AI, digital pathology foundation models, geometric deep learning and / or multi-modal learning.
 * Excellent programming skills and proficiency in deep learning frameworks such as PyTorch, with openness to learning new tools and technologies.
 * Strong communication and collaboration skills with the ability to communicate complex data insights and recommendations to cross-functional teams.
 * Strong research skills, evidenced by publications in leading scientific journals and / or conference presentations.

## Description

* Develop and apply AI / deep learning approaches to extract insights from digital pathology imaging datasets (e.g., H&E, IHC, mIF, Spatial transcriptomics).
 * Work with foundational models, including pre-trained, self-supervised, multi-purpose, and multi-modal models to advance generative AI applications in drug discovery.
 * Support imaging biomarker development efforts by analyzing pathology imaging data and collaborate with pathologists and translational teams to interpret image-derived biomarkers and biological findings.
 * Contribute to evaluation, validation, and benchmarking of image analysis algorithms and workflows.
 * Perform tissue segmentation, cell phenotyping, feature extraction, and spatial analysis using state-of-the-art computational approaches.
 * Stay current with advances in computational pathology, AI/ML, and spatial biology technologies; contribute to scientific publications; and present results at internal and external scientific conferences.


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