Full-time jobs in Memphis, TN

About the role

Jude Children's Research Hospital is seeking two Senior Image Data Scientists to design, develop, validate, document, and operate image-analysis pipelines and visualization solutions for biomedical imaging research. This role works closely with investigators, software engineers, data scientists, imaging facility scientists, and biostatisticians to translate scientific questions into reproducible, scalable analysis workflows using modern image analysis, statistical, computer vision, and machine learning approache The successful candidate will support image data management,   maintain   analysis   software and repositories, evaluate new methods and tools, and provide technical consultation and training to research teams. This role also serves as a   project lead   to coordinate image-analysis efforts, align related projects, and contribute to shared CBI infrastructure that supports routine and advanced bioimage analysis.

What you'll bring

• Bachelor's degree in applied mathematics, physics, chemistry, bioinformatics, computer science, data science, computer engineering or related field required.
• Minimum Requirement: Bachelor's degree with 3+ years of work experience in relevant area (e.g., applied mathematics, physics, chemistry, bioinformatics, computer science, data science, computer engineering) required.
• Experience Exception: Master's degree with 1+ years of relevant experience.
• Experience in image analyses, image data management, and programming (e.g., Python, R, Matlab, Java, C/C++).
• Proven performance in earlier role/comparable role.
• PhD in a relevant quantitative, computational, biomedical, or scientific field.
• Experience developing,   validating, and   maintaining   image-analysis pipelines for biological or medical imaging data.
• Strong programming skills in Python and experience with modern computer vision, machine learning, deep learning, or statistical image-analysis methods.
• Experience with emerging AI methods relevant to bioimage analysis, including vision transformers, foundation models, generative AI, large language models (LLMs), or agentic AI tools.
• Experience with scalable and reproducible scientific workflows (e.g.,   Snakemake,   Nextflow ), containers, version control, and HPC or cloud environments.
• Demonstrated experience using modern bioimaging tools, data standards, and open-source ecosystems such as   napari, ImageJ/Fiji,   Cellpose, SAM-family and related foundation segmentation models,   QuPath, BioFormats, OME-Zarr/NGFF, or similar platforms.
• Experience with large image data volumes, image data management, quality control, benchmarking, annotation strategies, and method evaluation.