Staff Research Scientist – Reconstruction Physics

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Staff Research Scientist – Reconstruction Physics based in Canada. We are seeking an internationally recognized scientific expert to lead pioneering research in medical image reconstruction and quantitative nuclear medicine imaging. In this senior research role, you will define scientific strategies, develop advanced reconstruction algorithms, and explore innovative physics-based methods that push the boundaries of imaging technology. Your work will help shape future product development while translating complex scientific advances into meaningful clinical applications. Collaborating with multidisciplinary teams and external research partners, you will influence technical roadmaps and advance the broader scientific community through publications, conferences, and professional organizations. You will also mentor researchers, champion scientific rigor, and foster innovation across organizational boundaries. This is an opportunity to combine deep technical expertise with scientific leadership and make a lasting impact on the future of medical imaging.

Scientific Strategy & Research Leadership: Define and lead strategic research programs in medical image reconstruction, quantitative imaging, and imaging physics. Identify emerging scientific opportunities, guide long-term research priorities, and influence future technology and product roadmaps. Algorithm Development & Technical Innovation: Design, prototype, and evaluate novel image reconstruction algorithms and physics-based imaging methods. Apply advanced numerical modeling, inverse problem techniques, optimization, and statistical approaches to address complex imaging challenges. Scientific Validation & Software Prototyping: Develop high-quality software prototypes to demonstrate, test, and validate new scientific concepts, ensuring methodological rigor and practical relevance. External Scientific Engagement: Represent the organization within scientific working groups, standards initiatives, professional organizations, and research communities. Publish findings in peer-reviewed journals, present at leading scientific conferences, and establish collaborations with academic institutions, government agencies, research consortia, and industry partners. Cross-Functional Collaboration: Work closely with engineering, clinical science, product management, and business teams to align research priorities with customer needs, clinical objectives, and market opportunities. Influence technical strategies across programs and serve as a trusted scientific advisor to internal stakeholders. Mentorship & Capability Development: Mentor scientists and engineers, encourage knowledge sharing, lead technical reviews, and promote scientific reproducibility, methodological excellence, and a culture of continuous innovation. Advancement of Quantitative Imaging: Contribute to the future direction of quantitative nuclear medicine imaging and reconstruction science by advancing research, sharing expertise, and fostering collaboration across the scientific community. Requirements: Education: An advanced degree in Biomedical Engineering, Physics, Computer Science, Applied Mathematics, or a related discipline. A PhD is strongly preferred. Medical Imaging Expertise: Deep knowledge of medical imaging algorithms and substantial experience in image reconstruction, with demonstrated scientific innovation and independent research leadership. Technical Proficiency: Strong foundations in numerical methods, inverse problems, numerical optimization, statistical modeling, and physics-based imaging approaches. Research Leadership: Proven ability to lead complex technical initiatives, establish research direction, coordinate multidisciplinary stakeholders, and deliver high-impact scientific outcomes. Communication & Collaboration: Excellent written and verbal communication skills, with the ability to explain complex technical concepts, build partnerships, and influence decisions across scientific and organizational boundaries. Preferred Imaging Specialization: Recognized expertise in SPECT or other tomographic imaging modalities, quantitative nuclear medicine imaging, and theranostics. Advanced Modeling Experience: Familiarity with Monte Carlo simulation and physics-based system modeling is highly desirable. Scientific Recognition: A strong record of influential peer-reviewed publications, invited presentations, patents, or other recognized scientific contributions. External Research Partnerships: Experience leading multi-institution research programs, external collaborations, or scientific working groups. Mentorship & Technical Influence: Demonstrated experience mentoring researchers and providing scientific leadership across teams or organizations. Emerging Technologies: Familiarity with machine learning and artificial intelligence methods relevant to medical imaging. Professional Approach: A commitment to scientific rigor, integrity, transparency, ownership, and collaborative problem-solving, combined with a passion for advancing scientific discovery beyond incremental product improvements. Benefits: Employment Type: Full-time position. Work Arrangement: Remote. Compensation: Salary details are not specified in the provided job description. Total Rewards: A comprehensive rewards package is referenced, although specific benefits and compensation components are not detailed. Career Development: Opportunities to lead high-impact scientific research, influence long-term technology strategy, and contribute to advances in quantitative medical imaging. Scientific Visibility: Opportunities to publish research, present at major conferences, participate in scientific working groups, and build collaborations across academia and industry. Collaborative Environment: Work alongside multidisciplinary experts in research, engineering, clinical science, and product development. Mentorship & Leadership: Opportunities to mentor scientific talent and strengthen research capabilities across teams. Relocation Assistance: Not provided.