Clinical Scientist - MR

GE HealthCare

United States

Remote

USD 120,000 - 180,000

Full time

6 days ago
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Job summary

GE HealthCare is seeking an MR Clinical Scientist or Researcher to advance MRI research through practical, hands-on work and close collaboration with external partners. You will bring diverse MR expertise, technical curiosity, and a can-do attitude to projects at GE HealthCare and with collaboration sites.

The role focuses on applying MRI, engineering, AI, and clinical workflows to design novel MR applications, automate exams, and support biomarker discovery and aging research.

Qualifications

  • Bachelor's degree in an engineering or science field such as Electrical Engineering, Biomedical Engineering, Computer Science, Applied Math, or Physics.
  • Strong background in image processing, deep learning image segmentation, quantitative imaging, and MR open-source post-processing pipelines.
  • Excellent coding skills and ability to quickly prototype in C++, Matlab, and Python.

Responsibilities

  • Provide technical expertise to optimize GEHC MR products and prototype software/tools for research collaborators.
  • Lead as GEHC technical representative for collaborative projects aligned with MR roadmap and goals.
  • Develop MR applications to automate exams and support biomarker discovery and multimodal analysis.
  • Publish research findings and contribute to patents.

Skills

MR Physics
Image processing
Deep learning
C++
Python
Matlab
Communication
Collaboration
Independent work
Prototype development

Education

Bachelor's degree in engineering/physics/biomedical field
Master's degree (preferred)

Tools

GEHC MR Systems
Open-source post-processing pipelines
Code prototyping environments

Job description

Job Description Summary

Are you energized by solving complex problems at the intersection of advanced MRI, innovation, and human longevity? We are looking for an MR Clinical Scientist or Researcher that can bring practical, hands-on experience beyond academic training, along with diverse MR expertise, technical curiosity, and a can-do attitude to GE HealthCare and our collaboration partner.

Job Description
Essential Responsibilities
  • Provide technical expertise and support to optimize the use of GEHC MR products, partnering with GEHC scientists to introduce appropriate prototypes, software, and off-line analysis tools to research collaborators and support related research.
  • Identify key customer needs and serve as the GEHC technical lead for collaborative research projects aligned with the GEHC MR roadmap and strategic goals, particularly in longevity and preventative health.
  • Serve as the primary GE HealthCare scientific and technical representative at a strategic research collaboration site, operating with a high degree of independence and ownership.
  • Apply expertise in MRI, engineering, AI, and clinical workflows to design and develop innovative MR applications that automate and simplify exams, enable biomarker discovery for aging and early disease detection, and support multimodal correlation with therapeutic interventions and lifestyle changes.
  • Develop selected capabilities as prototypes and release them to external GEHC collaborators in accordance with GEHC MR design controls.
  • Conduct original research that contributes to patent applications and joint scientific publications.
  • Support pre- and post-market evidence generation at collaborating institutions by partnering with MR Clinical Directors to align collaborations with GEHC product development priorities and institutional needs.
  • Support customer satisfaction through proactive communication, site observation, and timely escalation of site inquiries and concerns.
  • This role will need to be able to work onsite at a facility in Englewood , NJ
Qualifications/Requirements
  • Bachelor's Degree in an engineering or science field such as Electrical Engineering, Biomedical Engineering, Computer Science, Applied Math, or Physics.
  • Minimum 5 years of work experience in the medical imaging or medical research field post-graduation.
  • Strong preference for candidates with demonstrated industry experience applying MRI technologies within healthcare technology, medical imaging, clinical research, or commercial research environments beyond academic training alone.
  • Strong background in image processing, deep learning image segmentation, quantitative imaging, and MR open-source post-processing pipelines.
  • Strong understanding of MR Physics.
  • Familiarity with GEHC MR Systems and research conducted on those systems.
  • Substantial experience in software design, implementation, and coding.
  • Excellent coding skills and ability to quickly prototype in C++, Matlab, and Python.
  • Outstanding writing, presentation, and communication skills.
  • Strong collaboration skills and ability to thrive in a dynamic environment.
  • Demonstrated ability to work independently, manage competing priorities, and drive initiatives with minimal supervision.
  • Can-do attitude, flexibility, intellectual curiosity, and willingness to work with cross-functional global teams.
  • This role will need to be able to work onsite at a facility in Englewood , NJ
  • Willing to travel up to 10% outside of primary work location.
Desired Characteristics
  • Master's Degree in an engineering or science field such as Electrical Engineering, Biomedical Engineering, Computer Science, Applied Math, or Physics.
  • Experience in advanced MR methods such as diffusion imaging, quantitative imaging, and image segmentation/registration.
  • Hands-on experience with in-vivo MR imaging in a research setting.
  • Clinical or research MR experience across multiple anatomical areas, including neuro, body, musculoskeletal, and quantitative imaging applications.
  • Experience in the application of Machine Learning and Artificial Intelligence to medical imaging.
  • Experience in predictive modeling or multimodal analysis.
  • Familiarity with GEHC EPIC Pulse Sequence Development environment and GEHC Orchestra Reconstruction environment.

Demonstrated interest in longevity science, aging research, preventative health, precision

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