Senior Scientist II, Pathology

Company Description

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on X, Facebook, Instagram, YouTube, LinkedIn and Tik Tok.

Job Description

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, da