Senior Scientist II, Computational Pathology, Precision Medicine Pathology
About The Position
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.
Requirements
- Bachelors degree with 12 years of experience, Masters degree with 10 years of experience or a PhD or equivalent with 4 years of 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.
Nice To Haves
- Exposure to digital pathology or biomedical imaging, such as histopathology, microscopy, or tissue imaging datasets.
- Experience with spatial omics data or integrating molecular data with image analysis.
- Working knowledge of techniques in precision medicine, biomarker discovery, or personalized treatment strategies is a plus.
- Familiarity with cell and molecular biology concepts in fields like oncology, immunology, or cancer immunotherapy, or an eagerness to learn.
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.
Benefits
- paid time off (vacation, holidays, sick)
- medical/dental/vision insurance
- 401(k)
- long-term incentive programs
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
