Shanghai, Shanghai Shi
15 days ago
SSME DTI Research Scientist

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.

Your role:

Looking for talent to join our team now at Siemens Healthineers as Research Scientist As a Research Scientist, you will be part of the Digital Technology and Innovation Center, the central hub for R&D in artificial intelligence and digital innovation of Siemens Healthineers. Our global footprint extends to USA (Princeton, NJ), China, India, and various countries within Europe. Our highly skilled AI experts specialize in using large data collections and powerful supercomputing infrastructure to build artificial intelligence solutions. You will have the opportunity to test your knowledge in a challenging problem-solving environment. You will be encouraged to think out-of-the-box, innovate, and find solutions to real-life problems.
Mission: With advanced understanding of clinical customer and internal business partner needs, able to own and drive digital technology and innovative solution by design and implement deep learning based technical solutions. Primary Responsibilities: Work on large-scale data sets and real-world clinical problems Close collaboration with Siemens Healthineers Business lines to understand requirements and deliver successful AI solutions Close collaboration with clinical partners to understand the clinical problem and innovate for AI solutions Design, implement and validate algorithms in Deep Learning or traditional image processing methods to solve clinical demands Develop efficient metrics / evaluation criterion to judge algorithmic efficacy and performance based on clinical demands Continuously scouting the latest technology for technology trend analysis and selection of optimal technology for AI solutions Scientific publication and intellectual properties

Qualifications: Experience Strong technical background in Deep Learning and familiar with traditional image processing methods etc. Proficiency in Python and ability to quickly prototype in C++ is desired Experience in industry of building medical imaging solutions is preferred Research and internship experience in image segmentation, detection, classification, registration preferred Experience in medical image and medical big data preferred Outstanding written and verbal communication skills in English are required Excellent interpersonal and collaboration skills Strong ability to thrive and try to solve problems in a fast-paced environment Education Ph.D. in an engineering or science field such as Computer Science, Electrical Engineering, Statistics, or Applied Math. Alternative MSc. in an engineering or science field such as Computer Science, Electrical Engineering, Statistics, or Applied Math with at least 3 years industry experience.

Who we are:
We are a team of more than 71,000 highly dedicated Healthineers in more than 70 countries. As a leader in medical technology, we constantly push the boundaries to create better outcomes and experiences for patients, no matter where they live or what health issues they are facing. Our portfolio is crucial for clinical decision-making and treatment pathways.

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.

As an equal opportunity employer, we welcome applications from individuals with disabilities.

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