Associate Scientist, Informatics II

AbbVie•Worcester, MA

1d•$58,656 - $110,500•Onsite

About The Position

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.

Requirements

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.

Nice To Haves

Knowledge of molecular pathology techniques (e.g., immunohistochemistry, immunofluorescence, in situ hybridization etc.).
Experience with spatial transcriptomics images and multiplexed IF images
A foundation in biology or immunology is highly desirable, to support the development and interpretation of image analysis solutions for translational research

Responsibilities

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.