Asks for

The ad says“Experience with at least one relevant imaging modality or assay type, such as confocal microscopy, high-content imaging, or cell painting.”
The ad says“Experience with at least one relevant imaging modality or assay type, such as confocal microscopy, high-content imaging, or cell painting.”
The ad says“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.”
The ad says“Demonstrated experience developing quantitative image-analysis or computational solutions involving one or more of the following: image segmentation, feature extraction, phenotypic profiling, object classification, or analysis of high-content imaging data.”
The ad says“Demonstrated experience developing quantitative image-analysis or computational solutions involving one or more of the following: image segmentation, feature extraction, phenotypic profiling, object classification, or analysis of high-content imaging data.”
The ad says“Demonstrated experience developing quantitative image-analysis or computational solutions involving one or more of the following: image segmentation, feature extraction, phenotypic profiling, object classification, or analysis of high-content imaging data.”
The ad says“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.”
The ad says“Proficiency with the Python data-science ecosystem, including NumPy, pandas, Polars, scikit-learn, and/or PyTorch.”
The ad says“Demonstrated experience developing quantitative image-analysis or computational solutions involving one or more of the following: image segmentation, feature extraction, phenotypic profiling, object classification, or analysis of high-content imaging data.”
The ad says“Proficiency with the Python data-science ecosystem, including NumPy, pandas, Polars, scikit-learn, and/or PyTorch.”
The ad says“Demonstrated experience developing quantitative image-analysis or computational solutions involving one or more of the following: image segmentation, feature extraction, phenotypic profiling, object classification, or analysis of high-content imaging data.”
The ad says“Proficiency with the Python data-science ecosystem, including NumPy, pandas, Polars, scikit-learn, and/or PyTorch.”
The ad says“Proficiency with the Python data-science ecosystem, including NumPy, pandas, Polars, scikit-learn, and/or PyTorch.”
The ad says“Proficiency with the Python data-science ecosystem, including NumPy, pandas, Polars, scikit-learn, and/or PyTorch.”
The ad says“Demonstrated experience developing quantitative image-analysis or computational solutions involving one or more of the following: image segmentation, feature extraction, phenotypic profiling, object classification, or analysis of high-content imaging data.”
The ad says“Proficiency with the Python data-science ecosystem, including NumPy, pandas, Polars, scikit-learn, and/or PyTorch.”

Company Description

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.

Job Description

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, computer-vision, and machine-learning approaches to characterize cellular and tissue phenotypes, support the development of biological models, including co-cultures, organ-on-chip systems, organoids, and tissue explants, and generate insights that advance immunology discovery programs. This role combines hands-on delivery of robust, reproducible image-analysis workflows with the evaluation and application of advanced AI/ML approaches, including biomedical image segmentation, representation learning, foundation models, and scalable computational workflows. You will partner closely with wet-lab scientists, imaging specialists, computational scientists, and other subject-matter experts to translate biological questions into rigorous and impactful analysis strategies.

The role sits at the intersection of biology, bioengineering, microscopy, and computational science. Candidates with combined expertise in two or more of these areas are especially encouraged to apply.

Key Responsibilities

Develop, optimize, and apply imaging assays and quantitative image-analysis workflows for 2D and 3D cellular and tissue models to characterize cellular and other complex biological phenotypes.
Collaborate with wet-lab assay scientists, imaging specialists, and computational scientists from experimental and assay design through image acquisition, analysis, validation, and data delivery.
Extract biologically meaningful, multiparametric features from high-content imaging datasets and use them to characterize disease-relevant phenotypes, mechanisms, and treatment responses.
Apply statistical, machine-learning, and deep-learning methods to identify candidate imaging biomarkers and relate imaging phenotypes to molecular, functional, and other biological readouts.
Contribute to the integration of imaging data with multimodal datasets, including molecular, single-cell, spatial, or perturbational data, where appropriate.
Establish quality-control and evaluation frameworks to assess image and assay quality, distinguish biological signal from technical artifacts, and define data-quality criteria, acceptance thresholds, and analytical limitations.
Maintain clear experimental and analytical records; analyze, visualize, and present results rigorously to both technical and nontechnical audiences.
Communicate methods, assumptions, results, uncertainties, and limitations effectively to cross-functional project teams.
Stay current with advances in quantitative bioimaging, image analysis, computer vision, and AI/ML 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, bioinformatics, or a related discipline, with typically 10-12+ (BS), 8-10+ (MS), or 0-4+ (PhD) years experience.
Demonstrated experience developing quantitative image-analysis or computational solutions involving one or more of the following: image segmentation, feature extraction, phenotypic profiling, object classification, or analysis of high-content imaging data.
Experience with at least one relevant imaging modality or assay type, such as confocal microscopy, high-content imaging, or cell painting.
Ability to assess image quality, recognize common imaging 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

Experience working with complex in vitro models, such as organoids, organ-on-chip systems, co-cultures, tissue explants, or other advanced in vitro platforms.
Experience with classical bioimage-analysis tools such as CellProfiler, scikit-image, ImageJ/Fiji, or comparable platforms.
Exposure to deep-learning, self-supervised learning, foundation-model, embedding-based, or multimodal AI approaches for biological imaging.
Peer-reviewed publications, patents, conference presentations, or other demonstrated scientific contributions in quantitative bioimaging, computer vision, computational biology, bioengineering, or a related field.

Position will be filled at level commensurate with extent of education, experience, and accomplishment— Senior Scientist I or Senior Scientist II

Additional Information

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:

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.

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.

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.

US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:

https://www.abbvie.com/join-us/reasonable-accommodations.html