Eli Lilly and Company

Healthcare

PostdoctoralScientistCNSNeuroimaging&QuantitativeDataScience

$58–123k Boston, Massachusetts, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Postdoctoral Scientist – CNS Neuroimaging & Quantitative Data Science at Eli Lilly and Company. Skills: Neuroimaging, Quantitative data science, CNS therapeutics. Receive, organize, curate, and analyze multimodal CNS neuroimaging. Apply advanced quantitative analysis methods”

Industry & Context.

Healthcare
Problems you'll solve

Data-driven decision making

What They're Looking For.

Must Have

PhD in quantitative field, Demonstrated neuroimaging data handling, Standard preprocessing and quantitative analysis, Programming experience for image analysis, Experience working with large datasets, Communicating complex data

Nice to Have

PhD preferred, Specific ML framework experience, Cloud platform certs

What You'll Do.

and analyze multimodal CNS neuroimaging

Apply advanced quantitative analysis methods

Perform standard preprocessing and analysis workflows

Implement atlas-based registration and segmentation

multi-study imaging datasets

Develop and maintain custom Python-based image analysis workflows

Apply modern data analytics and visualization techniques

Lead co-registration and integration of neuroimaging data

Serve as a scientific bridge

Translate complex neuroimaging datasets

Act as a scientific interface

Clearly communicate imaging data needs

Collaborate with internal experts

Provide scientific and technical input to CROs

Contribute to optimization of imaging protocols

Ensure acquisition strategies support comparability

Contribute to the development of standardized

scalable neuroimaging

Explore and apply emerging neuroimaging and analytical approaches

How You'll Work.

Team & Collaboration

Internal experts; External CRO partners; Cross-functional scientific collaboration; Project teams; Leadership audiences; Lilly neuroscience teams; Genomic medicine teams

Communication Scope

Clear communication; Interpretable visualizations

Full Job Description

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world. Position Overview: Eli Lilly and Company is seeking a highly motivated Postdoctoral Scientist in CNS Neuroimaging to join the Drug Delivery and Connected Systems (DDCS) group. This role will support CNS therapeutic development by applying multimodal neuroimaging and quantitative data analytics across discovery and translational research programs. The successful candidate will play a critical role in enabling data‑driven decision making for CNS drug delivery strategies through the management, analysis, and interpretation of complex neuroimaging datasets derived from preclinical and in vivo studies. Imaging modalities may include MRI, CT, PET, optical imaging, and other emerging techniques relevant to CNS exposure, biodistribution, target engagement, and neurobiological response. This scientist will work closely with internal experts in neuroscience, drug delivery, genomics, and biodistribution, as well as with external CRO partners, to optimize imaging strategies, ensure data quality, and translate imaging outputs into actionable biological and therapeutic insights. This postdoctoral position offers the opportunity to work at the intersection of CNS therapeutics, multimodal neuroimaging, and quantitative data science within a leading pharmaceutical research organization. The role provides direct exposure to translational decision‑making, complex CNS drug delivery challenges, and cross‑functional scientific collaboration. There

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