Role Overview

At AbbVie, Preclinical Safety (PCS) is responsible for creating and executing development plans that support novel drug candidates from nonclinical testing through first-in-human, registration, and post-marketing phases. The Digital and Computational Pathology Laboratory in PCS is seeking a talented and motivated Data Scientist to develop cutting-edge methodologies in computer vision and AI to power whole slide image analyses in nonclinical drug development. The ideal candidate will possess a strong background in computer science, engineering, or a related field, with emphasis on computer vision and deep learning. The role involves designing and implementing algorithms for anomaly detection, segmentation, and classification to contribute to the development of accurate and efficient AI-assisted digital pathology readouts. Specific skills required include proficiency in programming languages such as Python and C++, as well as experience with machine learning frameworks like TensorFlow or PyTorch. Familiarity with image processing libraries and a solid grasp of deep learning models, including large vision models, are essential. Additionally, experience in curating and analyzing large-scale biomedical datasets is highly desirable. The candidate should have strong analytical skills, a track record of publication in high-impact journals, and an ability to work collaboratively within a multidisciplinary team.
 

Responsibilities

• Conceive, design and implement original technical ideas that solve significant scientific or business problems through the integration, visualization, and analysis of large and complex data, especially biomedical images. Routinely demonstrate initiative and creativity in developing technology solutions.
• Demonstrate high proficiency across a wide range of technologies related to the storage, transfer, integration, visualization, and analysis of large and diverse data sets. Expertise in software development, data warehousing, statistics, and AI/ML.
• Demonstrate deep knowledge of biomedical research and the pharmaceutical business, and utilize this knowledge in the rapid advancement of agile, impactful, and cost-effective solutions.
• Highly autonomous and productive in performing activities, requiring only minimal direction from or interaction with supervisor.
• Initiate new areas of investigation that are meaningful, reliable, and may be incorporated directly into a scientific or business activity.
• Direct mentorship of others.
• A primary author of publications and presentations; present at external scientific conferences.
• Understand and adhere to corporate standards regarding applicable Corporate and Divisional Policies, including code of conduct, safety, GxP compliance, and data security.