Associate Scientist, Informatics II

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.

The AbbVie Immunology Discovery pathology group is at the forefront of Artificial Intelligence driven digital pathology and committed to establishing quantitative and translational pathology end points to drive drug discovery research. We seek an innovative and highly motivated research scientist with expertise spanning digital pathology, image analysis, machine learning, artificial intelligence and scientific programming. The successful candidate will develop and deploy image analysis solutions to support quantitative pathology, spatial biology, and multi-modal omics studies. The scientist will work closely with pathologists, biologists, and data scientists to build scalable workflows for the analysis, integration, and management of large imaging datasets, including histology, multiplex immunofluorescence (mIF), spatial transcriptomics, and other emerging imaging technologies. This position is located in Worcester, MA.

Develop, validate, and deploy automated image analysis workflows for histopathology and spatial biology applications, using image analysis platforms (e.g. Visiopharm, Qupath) Design machine learning and deep learning approaches for cell segmentation, cell phenotyping, biomarker quantification, and spatial analysis. Employ appropriate validation methods for evaluating model performance Perform image registration, de-arraying, and alignment for multi-modal imaging datasets. Develop custom scripts, and automated pipelines using Python and related scientific computing libraries. Configure, monitor, and optimize scalable compute resources for high-throughput image processing. Architect and integrate multiple databases into a cohesive, scalable system, leveraging a strong understanding of database infrastructure. Troubleshoot complex software issues and collaborate directly with third-party software engineers to develop novel, tailored solutions Collaborate with multidisciplinary teams including pathologists, biologists, bioinformaticians, and computational scientists. Present analytical methods, results, and recommendations to scientific stakeholders. Maintain accurate documentation of workflows, algorithms, and study results. Contribute to publications, conference presentations, and scientific innovation initiatives.

Bachelor’s Degree in Computer Science, Data Science, Artificial Intelligence, Biology or related field, or equivalent education, with typically 3 or more years’ experience or Master’s Degree in Computer Science, Data Science, Artificial Intelligence, Biology or related field or equivalent education (no additional experience). Experience in the pharmaceutical industry is preferred. Demonstrated experience in digital pathology and image analysis platforms (Visiopharm, Halo, QuPath, Image J), plus a deep understanding of image analysis core concepts, including image processing and machine learning. Strong proficiency in Python and associated scientific computing libraries (NumPy, Pandas, SciPy, Scikit-learn, or similar). Working knowledge of cloud computing platforms (AWS), scalable computational workflows and database infrastructure Proficiency in the use of third-party software tools to support data analysis tasks (e.g., GraphPad Prism, Spotfire, Excel). Strong problem-solving, communication, documentation and collaboration skills. Desirable Knowledge of molecular