Senior AI Scientist - Medical Imaging - Generative AI at Siemens Medical Solutions USA, Inc. in Princeton, New Jersey

Job Description:

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.


Join our team now at Siemens Healthineers , Princeton, NJ, USA as Senior AI Scientist : " Medical Imaging (Generative AI) "


This is a role well suited to an ambitious professional, looking for the next step in their career. As a Senior AI Scientist , you will be responsible for :


• You will be working on large-scale, real-world problems, be entrepreneurial in an environment that is more startup than big company.


• You will work with customers to understand algorithm and workflow requirements and deliver solutions.


• You will conduct research, design, and implement disruptive algorithms for solving inverse problems ( beamforming, despeckling , deconvolution, super-resolution etc.) in Ultrasound Imaging using Deep Learning methods, such as Generative AI (Diffusion) .


• You will be involved in fast prototyping, feasibility studies, specification, and implementation of medical imaging product components.


• You will advance the state-of-the-art in the field, including generating patents and publications in top journals and conferences.


This position may suit you best ifyou are familiar with what is below and would like to do develop your career with Healthineers.


• You have a Ph.D. in an engineering or science field such as Electrical Engineering, Computer Science , Medical Physics, Biomedical Engineering etc.


• Strong theoretical background and expertise in Medical Physics ( esp. Ultrasound Physics ), Imaging Science, Computational Imaging


• 5+ years of experience (including Ph.D. study) and expertise in Machine Learning, Deep Learning, Inverse Problems


• Strong publication record in Machine Learning, Inverse Problems, Medical Imaging


• You have experience with machine learning libraries ( such as PyTorch , TensorFlow, Keras ) , advanced deep neural network models and in addition you are familiar with image processing in Python and C++


• Graduate research (and internship) experiences in Machine Learning, Inverse Problems, Medical Imaging preferred.


Required skills to have for the success of this role.


• You have a Ph.D. in an engineering or science field such as Electrical Engineering, Computer Science , Medical Physics, Biomedical Engineering etc.


• You have 5+ years of experience (including Ph.D. study) and expertise in Machine Learning, Deep Learning, Inverse Problems


• You will be working with our latest technology and therefore you are willing to learn about new software solutions.


• Outstanding collaboration, interpersonal and communication (verbal & written) skills in English is a must .


• You are a team player who can also be independent, prioritize work and thrive in a fast-paced dynamic environment.


• You have very good presentation skills in the customer environment, and you show team orientation, communication skills and customer orientation.


• You have the drive and motivation for career development and open to taking on challenges.


• Willing to travel up to 10%



How we work:
When you join Siemens Healthineers, you become one in a global team of scientists, clinicians, developers, researchers, professionals, and skilled specialists, who believe in each individual's potential to contribute with diverse ideas. We are from different backgrounds, cultures, religions, political and/or sexual orientations, and work together, to fight the world's most threatening diseases and enable access to care, united by one purpose: to pioneer breakthroughs in healthcare. For everyone. Everywhere. Sustainably. Check our Careers Site at https://jobs.siemens-healthineers.com/careers



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