Senior Computational Research Scientist - Department of Imaging Sciences

St. Jude
St. Jude logo
Location
Memphis, TN
Job Type
Full-time
Posted
September 16, 2026
Views
8
Salary Range
$104k - $186k USD

Job Description

AI and Computer Vision

for Biomedical Imaging

St. Jude Children’s Research Hospital | Memphis, Tennessee

Manor Laboratory • Department of Imaging Sciences • Full-time

Principal investigator: Uri Manor, Ph.D.

The Manor Laboratory seeks an experienced computational imaging professional to develop and apply artificial intelligence, computer vision, and quantitative image analysis to challenging questions in cell biology and biomedical research. Working closely with Dr. Uri Manor, experimental scientists, and collaborators, this individual will provide technical leadership across the laboratory’s computational imaging portfolio and translate advanced imaging data into validated biological measurements and broadly usable research tools.

The position spans fluorescence, label-free, live-cell, three- and four-dimensional (3D/4D), and electron microscopy. Applications include sensory-organ structure and pathology, cellular and organelle dynamics, and dense reconstruction of biological tissue. The role combines independent algorithm development, end-to-end scientific software engineering, collaborative research, and technical mentorship; it is not restricted to one disease, imaging modality, or biological system.

Key responsibilities

  • Guide computational imaging strategy

Partner with the principal investigator to prioritize and execute computer-vision and quantitative image-analysis projects across the laboratory. Translate biological questions into computational objectives, technical plans, and measurable deliverables. Establish reusable architectures, evaluation standards, and best practices that support consistent, reproducible analysis across imaging modalities and research programs.

  • Develop and validate AI methods

Design, implement, and benchmark methods for segmentation, classification, detection, tracking, image reconstruction and restoration, denoising, virtual staining, resolution enhancement, and quantitative phenotyping. Apply appropriate approaches, including convolutional and recurrent neural networks, Transformers, multimodal learning, generative models, and vision-language models. Evaluate performance on independent data, assess failure modes and generalizability, and verify that image transformations preserve biologically meaningful information.

  • Translate imaging data into biological insight

Develop 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

Lead end-to-end workflows spanning annotation strategy, dataset curation, model training, validation, deployment, and maintenance. Develop documented, tested, version-controlled software, including interactive desktop plugins and web-based analysis tools where appropriate. Optimize workflows for large, multidimensional datasets and GPU or parallel computing. Expand annotated resources, support generalizable models, and collaborate with institutional and external partners to make tools accessible, maintainable, and useful to researchers.

  • Mentor researchers and disseminate methods

Provide technical guidance and mentorship to students, postdoctoral fellows, staff, and collaborators developing or applying AI tools. Advise on experimental design, data preparation, annotation, model selection, code development, validation, interpretation, and reproducibility. Develop training materials, lead hands-on instruction, and support adoption of shared tools. Contribute to manuscripts, grant applications, scientific presentations, and collaborative methods development while fostering a supportive, interdisciplinary research environment.

Minimum Education Requirements

  • Bachelor's degree in Bioinformatics, Molecular Biology, Biochemistry, Computer Science, or related field.
  • Master's degree or PhD preferred.

AI and Computer Vision

for Biomedical Imaging

St. Jude Children’s Research Hospital | Memphis, Tennessee

Manor Laboratory • Department of Imaging Sciences • Full-time

Principal investigator: Uri Manor, Ph.D.

The Manor Laboratory seeks an experienced computational imaging professional to develop and apply artificial intelligence, computer vision, and quantitative image analysis to challenging questions in cell biology and biomedical research. Working closely with Dr. Uri Manor, experimental scientists, and collaborators, this individual will provide technical leadership across the laboratory’s computational imaging portfolio and translate advanced imaging data into validated biological measurements and broadly usable research tools.

The position spans fluorescence, label-free, live-cell, three- and four-dimensional (3D/4D), and electron microscopy. Applications include sensory-organ structure and pathology, cellular and organelle dynamics, and dense reconstruction of biological tissue. The role combines independent algorithm development, end-to-end scientific software engineering, collaborative research, and technical mentorship; it is not restricted to one disease, imaging modality, or biological system.

Key responsibilities

  • Guide computational imaging strategy

Partner with the principal investigator to prioritize and execute computer-vision and quantitative image-analysis projects across the laboratory. Translate biological questions into computational objectives, technical plans, and measurable deliverables. Establish reusable architectures, evaluation standards, and best practices that support consistent, reproducible analysis across imaging modalities and research programs.

  • Develop and validate AI methods

Design, implement, and benchmark methods for segmentation, classification, detection, tracking, image reconstruction and restoration, denoising, virtual staining, resolution enhancement, and quantitative phenotyping. Apply appropriate approaches, including convolutional and recurrent neural networks, Transformers, multimodal learning, generative models, and vision-language models. Evaluate performance on independent data, assess failure modes and generalizability, and verify that image transformations preserve biologically meaningful information.

  • Translate imaging data into biological insight

Develop 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

Lead end-to-end workflows spanning annotation strategy, dataset curation, model training, validation, deployment, and maintenance. Develop documented, tested, version-controlled software, including interactive desktop plugins and web-based analysis tools where appropriate. Optimize workflows for large, multidimensional datasets and GPU or parallel computing. Expand annotated resources, support generalizable models, and collaborate with institutional and external partners to make tools accessible, maintainable, and useful to researchers.

  • Mentor researchers and disseminate methods

Provide technical guidance and mentorship to students, postdoctoral fellows, staff, and collaborators developing or applying AI tools. Advise on experimental design, data preparation, annotation, model selection, code development, validation, interpretation, and reproducibility. Develop training materials, lead hands-on instruction, and support adoption of shared tools. Contribute to manuscripts, grant applications, scientific presentations, and collaborative methods development while fostering a supportive, interdisciplinary research environment.

Minimum Education Requirements

  • Bachelor's degree in Bioinformatics, Molecular Biology, Biochemistry, Computer Science, or related field.
  • Master's degree or PhD preferred.

Minimum Experience Requirements

  • Bachelor's degree and 7+ years of relevant experience.
  • Exception: Master's degree and 5+ years of relevant experience (OR) PhD with 2+ years of relevant experience.
  • Rough criteria for this position based on publication output: 1-2 first author papers IF > 10 (or equivalent contribution to other research outputs).
  • Prior experience in computational research techniques and processes.
  • Proven performance in earlier role/comparable role.

Preferred qualifications

  • 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.
  • Strong Python programming and experience with a major deep-learning framework such as PyTorch or TensorFlow; experience with MATLAB, C++, GPU computing, or parallel processing is advantageous.
  • 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 is particularly relevant.
  • 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 is beneficial.
  • 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 is helpful.

Compensation

In recognition of certain U.S. state and municipal pay transparency laws, St. Jude is including a reasonable estimate of the compensation range for this role. This is an estimate offered in good faith and a specific salary offer takes into account factors that are considered in making compensation decisions including but not limited to skill sets, experience and training, licensure and certifications, and other business and organizational needs. It is not typical for an individual to be hired at or near the top of the salary range and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current salary range is $104,000 - $186,160 per year for the role of Senior Computational Research Scientist - Department of Imaging Sciences.

Explore our exceptional benefits!

We are committed to a human-centered hiring experience. Technology may support portions of our process, but recruiting decisions involve human review and engagement. Learn more about our approach to AI.

St. Jude is an Equal Opportunity Employer

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St. Jude Children's Research Hospital does not accept unsolicited assistance from search firms for employment opportunities. Please do not call or email. All resumes submitted by search firms to any employee or other representative at St. Jude via email, the internet or in any form and/or method without a valid written search agreement in place and approved by HR will result in no fee being paid in the event the candidate is hired by St. Jude.

Frequently Asked Questions

Where is the job located, and is it remote/hybrid/on-site?
The job is located in Memphis, TN at St. Jude Children's Research Hospital. It is a full-time, on-site position within the Manor Laboratory in the Department of Imaging Sciences.
What are the key responsibilities of this role?
You will guide computational imaging strategy, develop and validate AI methods (like segmentation and image reconstruction), translate imaging data into biological insights, build reliable software and datasets, and mentor researchers on applying AI tools.
What are the minimum education and experience requirements?
You need a Bachelor's degree in a related field with 7+ years of experience, a Master's with 5+ years, or a PhD with 2+ years. You must also have prior computational research experience and 1-2 first-author papers with an impact factor over 10 (or equivalent output).
What preferred qualifications are you looking for?
Preferred qualifications include a PhD in a quantitative field, Python proficiency with PyTorch or TensorFlow, experience developing machine-learning methods for biomedical images, familiarity with 3D/4D microscopy or electron microscopy, and experience translating research prototypes into usable software.
What is the salary range for this position?
The estimated salary range for this role is $104,000 - $186,160 per year. The final salary offer will depend on factors such as skill sets, experience, training, and certifications.
Who will I report to and work with?
You will work closely with and report to the Principal Investigator, Dr. Uri Manor, while collaborating with experimental scientists and external partners.

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Job Information

Source: manual
AI Relevance: 88/100 (Highly relevant)
Remote Type: onsite
Allowed Locations: Worldwide
Skills & Tags:
st. jude artificial intelligence bioinformatics

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