Senior Computational Research Scientist - Department of Imaging Sciences

St. Jude Children's Research Hospital•Memphis, TN

2d•Onsite

About The Position

The Manor Laboratory in the Department of Imaging Sciences at St. Jude Children’s Research Hospital is seeking an experienced computational imaging professional. This role focuses on developing and applying artificial intelligence, computer vision, and quantitative image analysis to address complex questions in cell biology and biomedical research. The successful candidate will collaborate with Dr. Uri Manor, experimental scientists, and other researchers to provide technical leadership in computational imaging. This position involves translating advanced imaging data into validated biological measurements and creating broadly usable research tools. The work encompasses various imaging modalities including fluorescence, label-free, live-cell, 3D/4D, and electron microscopy, with applications in sensory-organ structure and pathology, cellular and organelle dynamics, and dense reconstruction of biological tissue. The role integrates independent algorithm development, scientific software engineering, collaborative research, and technical mentorship, and is not limited to a specific disease, imaging modality, or biological system.

Requirements

Bachelor's degree in Bioinformatics, Molecular Biology, Biochemistry, Computer Science, or related field.
7+ years of relevant experience with a Bachelor's degree.
OR 5+ years of relevant experience with a Master's degree.
OR 2+ years of relevant experience with a PhD.
Prior experience in computational research techniques and processes.
Proven performance in an earlier role/comparable role.
Strong Python programming.
Experience with a major deep-learning framework such as PyTorch or TensorFlow.

Nice To Haves

Master's degree or PhD preferred.
A Ph.D. in computer science, computer engineering, electrical engineering, biomedical engineering, applied mathematics, or a closely related quantitative field.
Demonstrated independent development and validation of machine-learning or computer-vision methods for biomedical images, supported by publications, deployed software, or comparable research outputs.
Experience with MATLAB, C++, GPU computing, or parallel processing.
Experience with 3D/4D microscopy, multichannel or multimodal imaging, segmentation, tracking, image restoration, or quantitative phenotyping.
Experience with electron microscopy, sparse annotations, or large volumetric datasets.
Ability to translate research prototypes into usable software, with experience in dataset curation, version control, testing, documentation, and reproducible workflows.
Experience with Napari or other interactive scientific analysis interfaces.
Effective interdisciplinary communication, collaborative problem-solving, and experience mentoring researchers or teaching computational methods.
Familiarity with cell biology, sensory neuroscience, organelle biology, spatial biology, or related biomedical applications.

Responsibilities

Guide computational imaging strategy by partnering with the principal investigator to prioritize and execute computer-vision and quantitative image-analysis projects.
Translate biological questions into computational objectives, technical plans, and measurable deliverables.
Establish reusable architectures, evaluation standards, and best practices for consistent, reproducible analysis across imaging modalities and research programs.
Develop and validate AI methods for segmentation, classification, detection, tracking, image reconstruction and restoration, denoising, virtual staining, resolution enhancement, and quantitative phenotyping.
Apply appropriate AI approaches, including neural networks, Transformers, multimodal learning, generative models, and vision-language models.
Evaluate method performance on independent data, assess failure modes and generalizability, and verify that image transformations preserve biologically meaningful information.
Translate imaging data into biological insight by developing quantitative analyses of multichannel 3D sensory-organ images and time-resolved cellular and organelle dynamics.
Advance dense 3D segmentation and reconstruction of serial-section electron-microscopy data, including approaches that learn from sparse two-dimensional annotations.
Work with experimental collaborators to connect computational outputs to interpretable measurements, rigorous biological conclusions, publications, and reusable research resources.
Build reliable software, datasets, and analysis platforms by leading end-to-end workflows from annotation strategy to model maintenance.
Develop documented, tested, version-controlled software, including interactive desktop plugins and web-based analysis tools.
Optimize workflows for large, multidimensional datasets and GPU or parallel computing.
Expand annotated resources, support generalizable models, and collaborate to make tools accessible, maintainable, and useful to researchers.
Mentor researchers and disseminate methods by providing technical guidance and mentorship to students, postdoctoral fellows, staff, and collaborators.
Advise on experimental design, data preparation, annotation, model selection, code development, validation, interpretation, and reproducibility.
Develop training materials, lead hands-on instruction, and support the adoption of shared tools.
Contribute to manuscripts, grant applications, scientific presentations, and collaborative methods development while fostering a supportive, interdisciplinary research environment.