Sr Scientist, Quantitative Bioimaging Full-time

Senior Scientist

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.

We are seeking a Senior Scientist to advance quantitative bioimaging capabilities in support of immunology discovery research. In this role, you will work within a cross-functional team with access to multiple microscopy modalities, complex in vitro models, multimodal biological datasets, and advanced computational infrastructure. You will develop and apply quantitative imaging and machine-learning approaches to characterize cellular and tissue phenotypes, support the development of complex in vitro models, and generate insights that advance immunology discovery programs. The role sits at the intersection of biology, bioengineering, microscopy, and computational science; candidates who have combined expertise in two or more of these areas are especially encouraged to apply. This position is onsite in Worcester, Massachusetts.

Key Responsibilities

• Develop, optimize, and apply imaging assays and quantitative image-analysis workflows for 2D and 3D cellular and tissue models across multiple microscopy platforms.
• Collaborate with wet-lab assay scientists, imaging specialists, and computational scientists from experimental design through image acquisition, analysis, and data delivery.
• Design and implement reproducible computer-vision and machine-learning pipelines for image segmentation, object detection, feature extraction, phenotypic profiling, and representation learning.
• Extract biologically meaningful, multiparametric features from high-content imaging datasets and use them to characterize disease-relevant phenotypes, mechanisms, and treatment responses.
• Establish practical quality-control and evaluation frameworks that assess image and assay quality, distinguish biological signal from technical artifacts, and define appropriate limitations and acceptance criteria.
• Apply statistical, machine-learning, and deep-learning methods to identify candidate imaging biomarkers and relate imaging phenotypes to molecular, functional, and other biological readouts.
• Maintain clear experimental and analytical records; analyze, visualize, and present results rigorously to both technical and nontechnical audiences.
• Stay current with advances in quantitative bioimaging, image analysis, computer vision, and foundation models for biological imaging, and evaluate opportunities to incorporate relevant approaches into team workflows.

Qualifications

Basic Qualifications

• BS, MS, or PhD in engineering, biophysics, computational biology, imaging science or a related discipline, with typically 10-12+ (BS), 8-10+ (MS), or 0-4+ (PhD) years experience.
• Demonstrated experience with microscopy, high-content imaging, quantitative image analysis, or phenotypic in vitro assay development.
• Experience working with at least one relevant imaging modality or assay type, such as confocal, high-content imaging, or cell painting. Candidates should be able to assess image quality, recognize common artifacts, and interpret biologically meaningful phenotypes.
• Working knowledge of machine-learning or deep-learning approaches for biological imaging, with the ability to understand model behavior, assess performance, and contribute to appropriate evaluation strategies.
• Proficiency with the Python data-science ecosystem, including NumPy, pandas, Polars, scikit-learn, and/or PyTorch.
• Strong biological grounding, attention to experimental rigor, and demonstrated ability to collaborate effectively with wet-lab and computational colleagues.
• Excellent written, verbal, and presentation skills, including the ability to explain methods, results, assumptions, and limitations to diverse audiences.

Preferred Qualifications

• Familiarity with complex in vitro models, such as organoids, organ-on-chip models and other advanced in vitro model platforms.
• Familiarity with image-based profiling, dimensionality-reduction methods, clustering, morphological feature analysis, or phenotypic similarity analysis.
• Peer-reviewed publications, patents, conference presentations, or other demonstrated scientific contributions in quantitative bioimaging, computer vision, computational biology, bioengineering, or a related field.

The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.

We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.

This job is eligible to participate in our short-term incentive program.

This job may be eligible to participate in our long-term incentive program.

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.

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Pay Range:

$ 109500 – 208500 USD

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USD

Where We Work

Role is exclusively performed at a site or office and onsite presence is required. Employees who are site/office-based and can occasionally perform their role virtually work both in the office and remotely*, following the policies and regulations in place at their location. US Employees must be in the office on Tuesday, Wednesday, and Thursday with flexibility to work remotely on Mondays and Fridays. Three days in the office is the minimum; some individuals or teams may require more in-office days due to meetings, business/project needs or their role.