Staff Research Scientist – Reconstruction Physics

# Job Description Summary
As a Staff Research Scientist – Reconstruction Physics, you will provide scientific leadership for next-generation reconstruction technologies in quantitative nuclear medicine imaging. You will lead research initiatives focused on SPECT image reconstruction, physics modeling, uncertainty quantification, and quantitative imaging methods, while helping shape both the GE HealthCare software product roadmap and the broader scientific direction of the field.

This role is intended for an internationally recognized expert who combines deep technical expertise with demonstrated influence across the research community. In addition to driving high-impact research programs, you will represent GE HealthCare through publications, scientific working groups, conference participation, and external collaborations that advance quantitative imaging science.

You will work closely with research, engineering, clinical science, product management, and external academic partners to translate emerging scientific advances into clinically meaningful innovations.

GE Healthcare is a leading global medical technology and digital solutions innovator. Our mission is to improve lives in the moments that matter. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference builds a healthier world.

Job Description

Roles and Responsibilities:

Scientific Leadership

- Define and lead strategic research programs in medical image reconstruction, quantitative imaging, and imaging physics.

- Establish scientific direction for reconstruction technologies that support future GE HealthCare product innovation, including our MIM Software product suite.

- Identify emerging scientific opportunities and guide long-term research investments in reconstruction and quantitative imaging.

- Lead cross-functional project teams, coordinating scientists, engineers, clinical experts, and external collaborators to deliver high-impact research outcomes.

Research and Technical Innovation

- Design, prototype, and evaluate novel reconstruction algorithms and physics-based imaging methods.

- Apply advanced modeling, inverse problem techniques, numerical optimization, and statistical methods to challenging imaging problems.

- Drive innovation beyond established approaches and contribute new scientific advances to the field.

- Develop high-quality software prototypes that demonstrate and validate new concepts.

External Scientific Leadership

- Maintain global expertise and scientific domain intellectual leadership both inside and outside GEHC.

- Represent GE HealthCare in scientific working groups, standards efforts, and professional organizations.

- Publish research findings in peer-reviewed journals and present results at leading scientific conferences.

- Build and maintain collaborations with academic institutions, research consortia, government agencies, and industry partners.

- Help shape the future direction of quantitative imaging and reconstruction science through visible technical leadership and community engagement.

Cross-Functional Influence

- Partner with clinical, engineering, product, and business leaders to align research strategy with customer and market needs.

- Influence technical roadmaps across multiple programs and organizational boundaries.

- Serve as a trusted scientific advisor to internal stakeholders and leadership teams.

Mentorship and Capability Building

- Mentor scientists and engineers across the organization.

- Promote scientific rigor, reproducibility, and technical excellence.

- Strengthen organizational capability through knowledge sharing, technical reviews, and research leadership.

Required Qualifications

- Advanced degree (PhD strongly preferred) in Biomedical Engineering, Physics, Computer Science, Applied Mathematics, or a related discipline.

- Deep expertise in medical imaging algorithms with significant experience in image reconstruction.

- Demonstrated record of scientific innovation and independent research leadership.

- Strong foundation in numerical methods, inverse problems, optimization, and statistical modeling.

- Experience leading complex technical initiatives involving multiple stakeholders.

- Excellent communication and collaboration skills.

Desired Characteristics

- Recognized expertise in SPECT or other tomographic imaging modalities.

- Expertise in Monte Carlo simulation and physics-based system modeling.

- Experience in quantitative nuclear medicine imaging and theranostics.

- Record of influential publications, invited presentations, patents, or other widely recognized scientific contributions.

- Experience leading external collaborations, multi-institution research programs, or scientific working groups.

- Experience mentoring researchers and providing technical leadership across organizations.

- Familiarity with machine learning and AI methods relevant to medical imaging.

You'll Thrive Here If You

- Are motivated to advance the state of the art, not just deliver incremental product improvements.

- Enjoy connecting academic innovation with meaningful clinical impact.

- Want to help define future scientific directions for quantitative imaging and reconstruction.

- Can influence technical strategy both inside and outside the organization.

- Value collaboration and enjoy building communities around important scientific challenges.

We expect all employees to live and breathe our behaviors: to act with humility and build trust; lead with transparency; deliver with focus, and drive ownership –always with unyielding integrity.

Our total rewards are designed to unlock your ambition by giving you the boost and flexibility you need to turn your ideas into world-changing realities. Our salary and benefits are everything you’d expect from an organization with global strength and scale, and you’ll be surrounded by career opportunities in a culture that fosters care, collaboration and support.

Additional Information

Relocation Assistance Provided: No