Career Category
Research
Job Description
At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.
Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. Amgen is advancing a broad and deep pipeline and portfolio of medicines to treat heart disease, obesity and obesity-related conditions, rare diseases, inflammatory conditions and cancer. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.
Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.
Senior Scientist, Computational Pathology and AI Informatics
What you will do
Let’s do this. Let’s change the world. We are seeking a Senior Scientist to join the Computational Imaging and Digital Biomarkers team. This hands-on role will develop and apply computational approaches to digital pathology and spatial biology data, with a strong focus on extracting biologically interpretable insights from tissue. You will integrate tissue morphology, cell phenotypes, spatial relationships, and molecular measurements to characterize the tumor microenvironment, investigate mechanisms of disease and drug response, and support biomarker discovery.
The role will also evaluate and apply H&E foundation models as reusable representations for image analysis and downstream biological questions. Working closely with pathologists, translational scientists, and computational biologists, you will translate research questions into rigorous, reproducible analyses and communicate what the results mean biologically.
Key Responsibilities
Design and apply spatial analysis approaches to characterize tissue organization, cellular composition and states, spatial neighborhoods, cell-cell interactions, distances, colocalization, and regional heterogeneity.
Work with pathologists and disease-area scientists to translate biological questions into analysis plans, select appropriate spatial statistics, and distinguish robust findings from technical or sampling artifacts.
Develop and apply computational pathology workflows for digitized H&E whole slide images, including tissue detection, tiling, quality control, feature extraction, segmentation, classification, and slide- or region-level modeling.
Evaluate and adapt H&E foundation models and learned representations for downstream tasks such as morphology characterization, clustering, prediction, and cross-modal association.
Apply approaches such as feature extraction, fine-tuning, weakly supervised learning, and multiple instance learning to adapt H&E foundation models to scientific questions and available datasets.
Assess model generalizability, interpretability, failure modes, and the relationship between model outputs and relevant biological or pathological features.
Design and execute analyses of spatially resolved tissue data, including multiplex immunofluorescence, high-plex imaging, and spatial transcriptomic or proteomic datasets.
Integrate spatial measurements with H&E morphology, IHC, clinical, molecular, and other biomarker data to generate biologically grounded, testable insights.
Develop visualizations and concise scientific narratives that connect computational results to tissue biology, mechanism of action, biomarker hypotheses, and program decisions.
Establish fit-for-purpose quality control, benchmarking, and validation approaches for spatial analyses.
Compare computational outputs with pathologist review, orthogonal assays, or other reference data, and communicate the strength and limitations of the evidence.
Build reproducible…