Postdoctoral Scientist – CNS Neuroimaging & Quantitative Data Science
Listed on 2026-06-03
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IT/Tech
Data Scientist, Data Science Manager, Data Analyst, Data Security
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.
Key ResponsibilitiesCNS Neuroimaging Data Management & Analysis
Receive, organize, curate, and analyze multimodal CNS neuroimaging datasets, including but not limited to MRI, CT, and complementary imaging approaches used in CNS drug delivery research. Apply advanced quantitative analysis methods across neuroimaging modalities relevant to regional CNS exposure, delivery efficiency, anatomical specificity, tissue response, and longitudinal change. Perform standard preprocessing and analysis workflows, including registration, segmentation, artifact assessment, and region‑based quantification.
Implement atlas‑based registration and segmentation using established CNS atlases (e.g., Allen Brain Atlas, Paxinos, and higher‑vertebrate atlases). Manage large, multi‑study imaging datasets with strong attention to data integrity, reproducibility, and documentation aligned with CNS research and regulatory expectations.
Demonstrate deep working knowledge of neuroimaging software platforms such as FSL, ANTs, ITK‑SNAP, and 3D Slicer. Develop and maintain custom Python‑based image analysis workflows and scalable pipelines tailored to CNS drug delivery research. Apply modern data analytics and visualization techniques to extract and communicate CNS‑relevant insights.
Multimodal Integration & Biological InterpretationLead co‑registration and integration of neuroimaging data with histology, IHC, and molecular biodistribution readouts. Serve as a scientific bridge between imaging and biodistribution teams, enabling coherent interpretation across spatial, anatomical, and molecular scales. Translate complex neuroimaging datasets into clear, interpretable visualizations and summaries for project teams and leadership audiences.
Cross‑Functional & External CollaborationAct as a scientific interface between DDCS, Lilly neuroscience and genomic medicine teams, and external CRO partners on neuroimaging strategy, data quality, and analytical approaches. Clearly communicate imaging data needs, timelines, and quality expectations to external collaborators while advocating for CNS program priorities. Collaborate with internal experts across neuroscience, gene therapy, toxicology, pharmacology, and bioinformatics to embed neuroimaging data into broader CNS therapeutic strategies.
ImagingAcquisition Strategy & Quality Optimization
Provide scientific and technical input to CROs to improve image quality, resolution, contrast, and interpretability for CNS applications. Contribute to optimization of imaging protocols addressing CNS‑specific challenges such as motion, susceptibility artifacts, small anatomical targets, and longitudinal consistency. Ensure acquisition strategies support cross‑study and cross‑site comparability.
Method Development & InnovationContribute to the development of standardized, scalable neuroimaging analysis pipelines tailored to CNS drug delivery and translational research. Explore and apply emerging neuroimaging and analytical approaches as appropriate to evolving CNS therapeutic modalities.
Basic Requirements- PhD in Imaging Sciences, Biomedical Engineering, Medical Physics, Neuroscience, Physics, Computer Science, or a closely related quantitative field.
- Demonstrated experience in neuroimaging data handling and analysis, including standard preprocessing and quantitative analysis techniques.
- Strong programming experience for image analysis, preferably in Python.
- Experience working with large datasets and communicating scientific insights through effective visualization.
- Abili…
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