Postdoctoral Fellow: Machine Learning in Digital Pathology

Johns Hopkins University

Baltimore (MD)

On-site

USD 63,000 - 77,000

Full time

4 days ago

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Job summary

The Johns Hopkins University School of Medicine invites a postdoctoral fellow with expertise in machine learning, computer vision, and image analysis to join a multidisciplinary research program focused on digital pathology and cancer research.

The fellow will develop novel algorithms for whole-slide image analysis, collaborate with pathologists and clinical investigators, and contribute to translational projects that may yield quantitative biomarkers and clinically meaningful AI approaches for

Qualifications

PhD in ML/CS/Computational Biology or related field.
Strong ML/deep learning background with hands-on model training.
Experience with image classification/segmentation in pathology.
Proficient in Python.
Experience with WSI handling and gigapixel images.

Responsibilities

Develop, implement, and validate machine learning models for image analysis.
Design computational pipelines for processing and analyzing digital pathology datasets.
Perform image segmentation, feature extraction, classification, and spatial analysis.
Develop reproducible computational workflows for large-scale image analysis.
Collaborate closely with pathologists to translate questions into computational approaches.
Analyze and interpret complex imaging and clinical datasets.
Contribute to manuscript preparation, grant applications, and presentations.
Mentor graduate students and research staff as appropriate.