Data Scientist, AI for Biomedical Imaging

Salary: £60,000 - 100,000 per year

Requirements:

• We require a PhD in computer science, AI, machine learning, biomedical image analysis, computational imaging, data science, or a related quantitative field, with 3+ years of applied experience in AI for bioimaging and computer vision.
• We require demonstrated experience developing and validating image analysis algorithms for biological, biomedical, or pharmaceutical research applications, with practical experience in image segmentation, feature extraction, phenotypic profiling, object classification, or representation learning applied to high-content or high-throughput imaging data.
• We require practical expertise in designing benchmarking and evaluation strategies to compare image analysis methods and guide rigorous, evidence-based model selection.
• We require ability to work effectively in Linux-based high-performance computing, cloud, or large-scale data processing environments, with a strong commitment to reproducible research, version control, testing, and data provenance.
• We require strong proficiency in Python and the scientific deep learning stack, along with hands-on experience using image analysis tools such as scikit-image, OpenCV, napari, Cellpose, StarDist, InstanSeg, and OME-Zarr.
• We require a self-motivated, experienced contributor who thrives in a collaborative, multidisciplinary environment with biologists, imaging scientists, software engineers, and bioinformatics partners, working with appropriate independence and helping shape project direction through both technical expertise and scientific judgment.
• We require excellent scientific communication and stakeholder engagement skills, including the ability to explain complex AI and image analysis concepts to experimental scientists, project teams, engineers, and non-technical audiences.
• We prefer experience developing or adapting foundation models, self-supervised learning approaches, multimodal AI models, or embedding-based analysis methods for biological imaging data.
• We prefer familiarity with the drug discovery pipeline, phenotypic screening, translational biology models, or pharmaceutical research processes.
• We prefer demonstrated success in turning project-specific solutions into reusable, scalable workflows or standardized analysis products integrated into enterprise platforms, production pipelines, or user-facing tools.
• We prefer a track record of scientific publication, conference presentations, open-source contributions, or internal technical leadership in AI, computer vision, biomedical image analysis, or related fields.
• We prefer familiarity with agentic coding tools and AI-assisted development workflows.

Responsibilities:

• We lead AI-enabled image analysis strategies for complex biological imaging workflows, acting as the embedded imaging-AI scientific partner working side-by-side with wet-lab scientists to understand emerging assay needs, align approaches with scientific priorities and platform standards, and explain advanced AI concepts in accessible terms.
• We identify high-impact opportunities where AI can deliver meaningful scientific value and define rigorous benchmarking and evaluation strategies to guide method selection.
• We develop, validate, and deploy robust image analysis algorithms to characterize cellular, organoid, tissue, and other complex biological phenotypes in high-throughput and high-content imaging data, generating reproducible outputs that support decision-making in drug discovery projects.
• We drive adoption of advanced AI methods for imaging, including deep learning, vision foundation models, embedding-based phenotyping, segmentation, classification, and multimodal integration, translating state-of-the-art methods into practical, validated workflows that augment expert review and enable scalable interpretation of large, high-dimensional datasets.
• We contribute to scalable, reusable image analysis workflows in partnership with other data scientists, data engineering, and platform teams, championing best practices across the workflow lifecycle.

Technologies:

• AI
• Cloud
• Computer Vision
• Embedded
• Support
• Linux
• Machine Learning
• Python
• opencv
• Claude Code
• Copilot
• PyTorch

More:

We are Novartis Biomedical Research in Cambridge, MA, and our mission is to reimagine medicine by advancing image analysis, computer vision, and AI methods for early drug discovery. We partner closely with experimental scientists, disease-area teams, data scientists, bioinformatics experts, and platform engineers to extract meaningful biological insight across diverse imaging modalities and biological model systems. This is an onsite, full-time role based in Cambridge, MA within our Discovery Sciences Data Science team. We offer a compensation package that includes a performance-based cash incentive, potential annual equity awards depending on role level, and for eligible US-based employees a comprehensive benefits package with health, life and disability benefits, a 401(k) with company contribution and match, and generous time off including vacation, personal days, holidays, and other leaves.

last updated 36 week of 2026