Associate Scientist, Post Doc Fellow- Computational Pathology & Spatial AI

MSD • Cambridge, MA

8d • $82,000 - $92,000 • Hybrid

About The Position

Within DAGS, our AI/ML team develops biologically grounded and interpretable machine learning methods to accelerate biomarker discovery across oncology. We are seeking a highly motivated Postdoctoral Research Fellow to develop next-generation multimodal AI approaches that integrate histopathology, transcriptomics, and spatial biology to characterize tumor microenvironment architecture and generate novel biological insights from routine H&E pathology images.

Requirements

• Must currently hold a PhD OR Receive a Ph.D. no later than spring 2027
• PhD in Computer Science, AI/ML, Computational Biology, Bioinformatics, Biomedical Engineering, Statistics, Applied Mathematics, or a related quantitative discipline.
• Computational Pathology, Deep Learning, Computer Vision, Multimodal AI, Transcriptomics, Foundation Models, Oncology, Tumor Microenvironment, Spatial Biology.
• Strong expertise in machine learning, deep learning, and data science.
• Proficiency in Python and deep learning frameworks such as PyTorch.
• Experience with computer vision, representation learning, multimodal modeling, or biomedical data analysis.
• Demonstrated research productivity through publications, preprints, or conference presentations.
• Ability to communicate complex technical concepts to multidisciplinary scientific teams.
• Academic Research
• Adaptability
• Bioinformatics
• Biological Imaging
• Computer Vision
• Data Analysis
• Machine Learning
• Scientific Research
• Transcriptomics

Nice To Haves

• Computational pathology.
• Spatial transcriptomics, RNA-seq, or single-cell omics analysis.
• Foundation models, transformers, and multimodal learning.
• Tumor microenvironment biology and oncology biomarker discovery.
• Publications in venues such as MICCAI, CVPR, NeurIPS, ISMB, AACR, or related journals.

Responsibilities

• Advance AI/ML methods that connect pathology images with molecular and spatial biology data.
• Develop interpretable computational approaches to study tissue organization, tumor microenvironment biology, and disease-relevant patterns.
• Integrate multimodal datasets to support biomarker discovery and biological hypothesis generation.
• Collaborate with multidisciplinary teams across data science, pathology, biology, and translational research.
• Communicate scientific findings through presentations, publications, and cross-functional discussions.

Benefits

• medical, dental, vision healthcare and other insurance benefits (for employee and family)
• retirement benefits, including 401(k)
• paid holidays
• vacation
• compassionate and sick days
• annual bonus
• long-term incentive

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree