Senior Scientist II, Computational Pathology, Precision Medicine Pathology

About AbbVie 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 including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com . Follow @abbvie on LinkedIn, Facebook , Instagram , X and YouTube.

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.

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.

Required Qualifications: Ph.D. in Computer Science, Electrical Engineering, Computational Biology, Bioinformatics, or related field with an emphasis on computer vision or machine learning; OR M.S. with 5+ years of relevant industry experience. Experience in image analysis techniques, including segmentation, object detection, and classification, evidenced by publications, open-source projects, or product development. Proficiency in programming languages like python and demonstrated experience using computer vision libraries such as OpenCV and ML frameworks like TensorFlow and PyTorch. Familiarity with MLOps practices, including deployment, monitoring, and lifecycle management of machine learning models in production environments. Familiarity with cloud computing platforms and scalable AI/ML pipelines (e.g., AWS, Azure, GCP). Excellent communication skills, including the ability to contribute to collaborative projects and explain technical concepts to interdisciplinary teams. Strong problem-solving skills and demonstrated creative approaches to overcoming challenges.

Exposure to digital pathology or biomedical imaging,