Sr Associate– Image Analysis & Digital Pathology

Overview

Senior Associate role on Amgen's Computational Imaging and Digital Biomarkers team, developing and applying computational pathology and AI/ML methods to support translational research, biomarker discovery, and precision medicine.

What you'll do

• Develop and apply image analysis, computer vision, and machine learning methods for digital pathology datasets.
• Design and implement analysis pipelines for whole-slide imaging (WSI), H&E, IHC, multiplex immunofluorescence, and spatial omics datasets.
• Build reproducible and scalable workflows using Python and modern ML/DL frameworks such as PyTorch or TensorFlow.
• Perform tissue segmentation, cell phenotyping, feature extraction, and spatial analysis using state-of-the-art computational approaches.
• 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.
• Support deployment and operationalization of computational imaging pipelines in cloud or high-performance computing environments.
• Stay current with advances in computational pathology, AI/ML, and spatial biology technologies.

What you'll need

• PhD or MS in Computer Science, Biomedical Engineering, Computational Biology, Bioinformatics, Electrical Engineering, Applied Mathematics, or related quantitative discipline.
• Strong background in computer vision, image analysis, and machine learning/deep learning.
• Demonstrated experience working with biomedical imaging data (pathology preferred).
• Proven track record in developing, validating, and deploying advanced computer vision and deep learning algorithms, including contributions to released products.
• Proficiency in Python and common ML frameworks (e.g., TensorFlow, PyTorch).
• Deep understanding of image analysis methods such as segmentation, object detection, and classification, ideally within digital pathology (e.g., histopathology, tissue imaging) and/or spatial omics.
• Familiarity with large-scale data management and cloud-based computational environments.
• Strong communication and interpersonal skills.

Nice to have

• 3+ years of experience in computational imaging, digital pathology, or medical image analysis.
• Strong programming skills in Python and experience with scientific computing libraries.
• Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow.
• Experience analyzing pathology imaging modalities including H&E, IHC, multiplex IF, or spatial transcriptomics data.
• Familiarity with whole-slide imaging tools and digital pathology platforms such as QuPath, HALO, Visiopharm, or OpenSlide.
• Understanding of machine learning methods for segmentation, classification, detection, and representation learning.
• Strong communication and collaboration skills in multidisciplinary scientific environments.
• Track record of scientific publications, conference presentations, or applied translational research contributions.

Details

• Location: Hyderabad, India.