Job Description

As a highly motivated ML/AI scientist at AbbVie Precision Medicine Pathology, you will be part of the computational pathology group dedicated to revolutionizing digital pathology and precision medicine. Your role will involve driving tissue-based translational and biomarker efforts for pre-clinical and clinical stage programs. You will be expected to have a passion for research, a track record of productivity, and accomplishments. Working in a fast-paced and dynamic environment, you will provide scientific leadership to guide teams in quantitative image-derived data generation and interpretation.

Key Responsibilities:

• Lead the design, development, and deployment of state-of-the-art machine learning algorithms including deep learning, representation learning, and self-supervised learning to address challenges in tissue image analysis, segmentation, and classification.
• Develop interpretable AI approaches by integrating attention mechanisms or explainable AI (XAI) techniques for clinical validation and adoption.
• Evaluate large-scale histopathology and spatial omics datasets to identify biomarkers for patient stratification and companion diagnostics.
• Collaborate cross-functionally with pathologists, biologists, statisticians, data analysts, and fellow scientists to seamlessly integrate ML/AI solutions into workflows and pipelines.
• Manage external collaborations with research partners to enhance project outcomes and foster innovation.
• Mentor and guide junior AI scientists and engineers, fostering a collaborative and innovative environment.
• Publish research findings in top-tier journals and conferences and present work to internal and external stakeholders.
• Stay updated on advancements in AI, computer vision, and digital pathology to continuously refine and expand the impact of your work.

Qualifications

Required Qualifications:

• Ph.D. in Computer Science, Electrical Engineering, Computational Biology, Bioinformatics, or related field with an emphasis on computer vision or machine learning with 6+ years of relevant industry experience; or M.S. with 12+ years of relevant industry experience; or BS or equivalent education and extensive, typically 14+ years of experience.
• Demonstrated expertise in developing, validating, and deploying advanced computer vision and deep learning algorithms, with successful product releases.
• Proficiency in Python, C++, and experience with computer vision libraries like OpenCV and ML frameworks such as TensorFlow and PyTorch.
• Strong experience in image analysis and techniques like segmentation, object detection, and classification, preferably in digital pathology or spatial omics.
• Experience with MLOps practices, including deployment, monitoring, and lifecycle management of ML models in production environments.
• Knowledge of cloud computing platforms and scalable AI/ML pipelines (e.g., AWS, Azure, GCP).
• Excellent communication skills, ability to convey complex technical concepts to non-technical stakeholders, and proven scientific writing ability.
• Strong problem-solving skills, creative approaches to challenges, excellent organizational skills, and ability to manage multiple projects simultaneously.

Preferred Qualifications

• Experience handling large-scale heterogeneous biomedical data with a focus on image processing and clinical data integration.
• Experience with spatial omics datasets and integrating molecular data with image analysis.
• Understanding of precision medicine applications, including biomarker discovery, patient stratification, and personalized treatment strategies.
• Desire and ability to learn, understand, and master new techniques or technologies.
• Familiarity with cell and molecular biology concepts relevant to immunology, cancer immunotherapy, or oncology, or a strong willingness to learn about these areas. Job Description:

As a highly motivated ML/AI scientist at AbbVie Precision Medicine Pathology, you will be part of the computational pathology group dedicated to revolutionizing digital pathology and precision medicine. Your role will involve driving tissue-based translational and biomarker efforts for pre-clinical and clinical stage programs. You will be expected to have a passion for research, a track record of productivity, and accomplishments. Working in a fast-paced and dynamic environment, you will provide scientific leadership to guide teams in quantitative image-derived data generation and interpretation.

Key Responsibilities:

• Lead the design, development, and deployment of state-of-the-art machine learning algorithms including deep learning, representation learning, and self-supervised learning to address challenges in tissue image analysis, segmentation, and classification.
• Develop interpretable AI approaches by integrating attention mechanisms or explainable AI (XAI) techniques for clinical validation and adoption.
• Evaluate large-scale histopathology and spatial omics datasets to identify