PET Scientist

Requirements

• Experience with PET image reconstruction and image correction methodologies.
• Experience with quantitative imaging and image quality assessment.
• Experience utilizing Monte Carlo simulation tools for imaging system modeling and evaluation.
• Experience with detector physics, acquisition systems, or imaging instrumentation.
• Publication record in peer-reviewed scientific journals and presentations at technical conferences.
• Experience contributing to patents, invention disclosures, or technology commercialization efforts.
• To find out more about Siemens Healthineers businesses, please visit our company page here .
• The base pay range for this position is:
• $119,920 - $164,890
• Factors which may aff

Benefits

Additional Information

Join us in pioneering breakthroughs in healthcare. For everyone. Everywhere. Sustainably. Our inspiring and caring environment forms a global community that celebrates diversity and individuality. We encourage you to step beyond your comfort zone, offering resources and flexibility to foster your professional and personal growth, all while valuing your unique contributions. The PET Physics team is actively involved across multiple stages of the PET development lifecycle, from detector technology through image formation and quantitative image analysis. The team is focused on developing innovative image reconstruction, data correction, and imaging physics solutions that enable high-quality, quantitatively accurate PET imaging. This role is well suited for an ambitious scientist seeking to contribute to the advancement of next-generation PET technologies while working in a highly collaborative and innovative research environment. You are responsible for: Supporting the technology and innovation roadmap for the PET Physics and Reconstruction team. Contributing to hardware innovation efforts across detector systems, analog electronics, digital electronics, acquisition systems, and overall PET system design. Developing and optimizing software innovations including PET data correction methods, image processing techniques, and analytical and statistical image reconstruction algorithms. Performing research and development activities related to image formation, quantitative imaging, and PET system performance. Collaborating closely with cross-functional R&D teams, product management, and engineering groups to transfer innovative technologies into commercial product solutions. Conducting simulation, experimental, and analytical studies to evaluate and improve PET imaging performance. Supporting the design, execution, and analysis of laboratory and system-level experiments. Publishing scientific results through peer-reviewed journals, technical conferences, and industry presentations. Contributing to intellectual property development through invention disclosures and patent activities. Participating in customer visits, scientific collaborations, and domestic and international conferences as required. This position may suit you best if: Iterative image reconstruction methods and image formation techniques. Statistical and analytical approaches to medical image reconstruction. Monte Carlo simulation methodologies. Experimental design, testing, and data analysis. Medical imaging physics and quantitative imaging principles. Software development in scientific and research environments. Collaborative research within multidisciplinary and geographically distributed teams. Working independently to solve complex technical challenges and drive innovative solutions. Required Qualifications: Ph.D. in Physics, Mathematics, Electrical Engineering, Nuclear Engineering, Medical Physics, or a related technical discipline. Experience in medical imaging, preferably PET imaging. Experience developing software using multiple programming languages, preferably including C++. Experience conducting research in one or more of the following areas: PET Imaging Image Reconstruction Medical Imaging Physics Radiation Physics Nuclear Physics Particle Physics Computational Imaging Related scientific fields

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