Senior Data Scientist, Imaging Foundation Models

Job Description

Within DAGS, our AI/ML team drives innovation across disease areas by building biologically grounded and interpretable imaging pipelines. In Immunology, digital pathology plays a critical role in understanding tissue level immune mechanisms and supporting companion diagnostics. We are seeking a Senior Data Scientist with strong expertise in computer vision and biomedical imaging to develop scalable imaging foundation models and interpretable pipelines for immunology and oncology biomarker discovery. 

 

What You’ll Do 

• Develop and train imaging foundation models for histopathology, with a focus on immune‑relevant tissue and cellular patterns. 

• Build segmentation driven and cell‑centric pipelines (e.g., immune cell typing, spatial organization, microenvironment analysis). 

• Design interpretable modeling workflows that link image derived features to biological hypotheses and clinical endpoints. 

• Apply zero‑shot and weakly supervised learning methods to extract immune signals from H&E and IHC data. 

• Collaborate closely with immunologists, pathologists, and translational teams to ensure biological relevance and interpretability. 

• Support imaging biomarker development efforts, including applications toward companion diagnostics. 

• Contribute to platform level imaging strategies, QC standards, and best practices within DAGS. 

• Share findings through internal forums, publications, and scientific collaborations. 

 

You Should Have 

• PhD in Computer Science, Engineering, Data Science, AI/ML, Bioinformatics, Computational Biology, Genetics & Genomics, Mathematics, Statistics, Physics, Pharmaceutical Science, or related STEM field with 0+ years postdoctoral experience or Master’s degree with 4+ years of industry experience.

• Strong expertise in computer vision and medical image analysis and/or multimodal data. 

• Experience building and/or applying models for segmentation, detection, and representation learning, ideally in histopathology. 

• Familiarity with modern deep learning architectures (e.g., transformers, vision foundation models). 

• Proficiency in Python and deep learning frameworks such as PyTorch. 

• Strong interest in immunology and tissue‑based biomarker discovery. 

• Ability to communicate complex technical ideas to multidisciplinary scientific partners. 

 

Preferred Skills and Experience 

• Familiarity with clinical or translational imaging biomarker programs. 

• Publications in venues such as MICCAI, CVPR, NeurIPS, ISBI, or related journals. 

#EligibleforERP

Required Skills:

Biomedical Imaging, Computer Science, Computer Vision, Data Science, Data Segmentation, Deep Learning, Digital Pathology, Foundation Models, Image Analysis, Machine Learning (ML), Medical Imaging Analysis, Multimodal, Multimodal Analysis, PyTorch, Representation Learning, Transformer Model, Vision Transformer (ViT)

Preferred Skills:

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