Digital Pathology & AI Image Analysis Scientist

AbbVie Inc.; Worcester (MA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Comprehensive benefits package

Paid time off

401(k) retirement plan

Job summary

AbbVie Inc. is seeking a research scientist in Worcester, MA, to advance digital pathology and spatial biology using AI-driven image analysis. You will work with pathologists, biologists, and data scientists to deploy scalable workflows for large imaging datasets, including histology and multiplex immunofluorescence.

The role emphasizes Python-based analysis, cloud computing, and integration of diverse data sources, with opportunities to contribute to publications and scientific initiatives.

Qualifications

• Bachelor’s or Master’s degree in a related field with relevant experience.
• 3+ years’ experience in digital pathology or image analysis.
• Proficiency in Python and scientific computing libraries.

Responsibilities

• Develop, validate, and deploy automated image analysis workflows for histopathology and spatial biology.
• Design machine learning/deep learning approaches for cell segmentation and biomarker quantification.
• Collaborate with pathologists, biologists, and data scientists to build scalable workflows for large imaging datasets.
• Configure and optimize scalable compute resources for high-throughput image processing.
• Integrate multiple databases and ensure robust data management.

Skills

Python programming

Machine learning

Image analysis

Data analysis

Team collaboration

Education

Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Biology or related field

Master's degree in Computer Science, Data Science, Artificial Intelligence, Biology or related field

Tools

Visiopharm

Halo

QuPath

ImageJ

AWS

GraphPad Prism

Spotfire

Excel

Job description

AbbVie Inc. is seeking a research scientist in Worcester, MA, to advance digital pathology and spatial biology using AI-driven image analysis. You will work with pathologists, biologists, and data scientists to deploy scalable workflows for large imaging datasets, including histology and multiplex immunofluorescence.

The role emphasizes Python-based analysis, cloud computing, and integration of diverse data sources, with opportunities to contribute to publications and scientific initiatives.