AbbVie Precision Medicine Pathology organization is committed to driving tissue based translational and biomarker efforts for our pre-clinical and clinical stage programs. We are seeking a talented and motivated Machine Learning (ML) Scientist to develop and apply advanced Artificial Intelligence (AI) techniques for analyzing complex histopathology and spatial omics datasets. This is a hands-on role ideal for candidates who are passionate about learning, collaborating, and driving innovation in the exciting intersection of machine learning, digital pathology, and precision medicine.
As a computational pathology scientist, you will be an integral part of a highly cross-functional team, working closely with colleagues from pathology laboratories and collaborating with research pathologists and assay scientists. You will engage with investigators involved in both discovery and late-stage research across a spectrum of disease areas, including oncology, cancer immunotherapy, immunology, and neuroscience, leveraging your AI expertise to advance our team's research objectives.
Key Responsibilities:
Develop, train, and validate machine learning models for tissue image analysis, including segmentation, object detection, and classification.
Apply advanced techniques such as deep learning and representation learning to solve key challenges in digital pathology.
Curate and maintain large-scale pathology datasets, ensuring data quality and integrity for robust model training and evaluation.
Develop and implement tools and pipelines for data preprocessing, feature engineering, and model deployment.
Collaborate with pathologists, biologists, statisticians, data analysts, and fellow engineers to integrate machine learning solutions into existing workflows.
Assist in external collaborations with research partners to enhance project outcomes and foster innovation.
Assist in evaluating histopathology and spatial omics datasets to identify biomarkers that inform patient stratification and companion diagnostic efforts.
Stay updated on the latest developments in AI, machine learning, and digital pathology techniques, and bring these insights to ongoing projects.
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