Senior Computational Imaging Scientist (Cloud AI)

BioSpace; Indianapolis (IN); On-site; USD 129,000 - 211,000; Full time

Job summary

Lilly seeks a hands-on computational imaging scientist to design, validate, and deploy enterprise-scale imaging solutions. You will work across histology and fluorescence modalities, building cloud-based pipelines with QC and traceability while applying ML/AI techniques to generate decision-driving insights.

Collaboration with bench scientists and partners is essential for translational impact. Applicants should hold a PhD in a quantitative field and have deep experience in Python/R,

Qualifications

• PhD in Computational Biology, Bioinformatics, Computer Science, Biomedical Engineering, Quantitative Biology, Data Science, or related quantitative field.
• Demonstrated experience designing, developing, validating, and deploying computational image-analysis workflows.
• Strong Python and R with software engineering practices and containerization (Docker preferred).
• Experience with AI coding assistants and agentic AI systems; validation of AI-generated code.

Responsibilities

• Design, validate, and deploy quantitative image-analysis workflows for histology and fluorescence imaging.
• Build reproducible, cloud-based pipelines with rigorous QC and traceability.
• Apply computer vision, ML, and generative models to practical biomedical problems.
• Collaborate with bench scientists and manage external collaborations and CROs.

Skills

Python

R

Git

Docker

Code review

Testing

Documentation

Education

PhD in Computational Biology, Bioinformatics, Computer Science, Biomedical Engineering, Quantitative Biology, Data Science, or related field

Tools

HALO

Visiopharm

Arivis Pro

AtoMx

QuPath

Job description

Lilly seeks a hands-on computational imaging scientist to design, validate, and deploy enterprise-scale imaging solutions. You will work across histology and fluorescence modalities, building cloud-based pipelines with QC and traceability while applying ML/AI techniques to generate decision-driving insights.

Collaboration with bench scientists and partners is essential for translational impact. Applicants should hold a PhD in a quantitative field and have deep experience in Python/R,