Lead Image Analysis Scientist, Digital Pathology & Omics

BioSpace; Worcester (MA); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

Paid time off

Medical/dental/vision insurance

401(k) plan

Long-term incentive programs

Job summary

AbbVie in the United States seeks an experienced Image Analysis Scientist to lead AI-driven digital pathology projects. You will apply deep learning, computer vision, and spatial analysis to quantify cell populations and tissue organization from H&E and immunolabeled sections.

You will develop scalable computational workflows, work with pathologists and discovery scientists, and stay at the forefront of AI advances to enable innovative drug discovery.

Qualifications

• PhD in computational biology, biomedical engineering, computer science, AI/ML, CV, or related field with 4+ years of applied experience.
• Strong foundation in math, statistics, image processing, ML/CV, and quantitative methods.
• Proven experience extracting features from histopathology imaging (H&E, IHC, multiplex).
• Proficiency in Python for scientific computing and ML, with libraries like NumPy, pandas, SciPy, scikit-learn, OpenCV, PyTorch, TensorFlow.

Responsibilities

• Design, develop, validate ML/CV approaches for digital pathology, including segmentation and cell phenotyping.
• Develop end-to-end image analysis workflows for high-dimensional imaging datasets.
• Apply rigorous model validation and statistical methods.
• Create reproducible computational workflows and well-documented code.

Skills

Python

Deep learning

Computer vision

Machine learning

Statistical methods

Education

PhD in computational biology or related field

Tools

PyTorch

TensorFlow

OpenCV

QuPath

Visiopharm

Job description

AbbVie in the United States seeks an experienced Image Analysis Scientist to lead AI-driven digital pathology projects. You will apply deep learning, computer vision, and spatial analysis to quantify cell populations and tissue organization from H&E and immunolabeled sections.

You will develop scalable computational workflows, work with pathologists and discovery scientists, and stay at the forefront of AI advances to enable innovative drug discovery.