Siemens Careers

Sr. Research Scientist – New Technologies for Patient-Specific Multi-Scale Modeling

Princeton, New Jersey
Research & Development

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English (US)

Job Description

Division: Siemens Healthineers
Business Unit: Strategy & Innovation
Requisition Number: 229488
Primary Location: United States-New Jersey-Princeton
Assignment Category: Full-time regular
Experience Level: Senior level
Education Required Level: Doctorate Degree
Travel Required: No

Division Description:

At Siemens Healthineers, we are passionate about enabling healthcare professionals to deliver high quality patient care, and to do so affordably.  A leading global med-tech company, Siemens Healthineers continues to strengthen our portfolio of medical imaging and laboratory diagnostics, while adding new offerings such as managed services, consulting, and healthcare IT services – as well as further technologies in the growing market for therapeutic and molecular diagnostics.

 

Siemens Healthineers develops innovations that support better patient outcomes with greater efficiencies, giving providers the confidence they need to meet the clinical, operational and financial challenges of a changing healthcare landscape.


For more information, please visit: 

http://www.usa.siemens.com/healthineers

Job Description:

Job description

The Digital Technology and Innovation team of Siemens Healthcare, Digital Services, has an immediate opening for a senior research scientist with a focus on new technologies for multi-scale modeling of organ functions, including but not limited to biophysical modeling, medical image and signal analysis and artificial intelligence. Our Princeton facility is recognized for providing a stimulating environment for highly talented and self-motivated researchers. 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. You will also be encouraged to publish your work in leading journals and conferences.

What are my responsibilities?

·        Research, design and implement algorithms with focus on fast and patient-specific computational modeling of biophysical systems

·        Research methods combining medical image and signal integration, computational modeling and artificial intelligence for fast prediction

·        Advance the state-of-the-art in the field, including generating patents and publications in top journals and conferences

·        Quick prototyping, feasibility studies, specification and implementation of software components

·        Work with customers and physicians to understand requirements, design evaluation studies and deliver high-quality solutions

What do I need to qualify for this job?

·        Ph.D. in Biomedical Engineering, Applied Mathematics, Computer Science or related discipline

·        3-5+ years of experience (including Ph.D. study), with strong knowledge in computational modeling and solvers for medical applications (biomechanics, electrophysiology, heat transfer, multi-scale models)

·        Expertise in medical image / signal analysis and artificial intelligence (deep learning, deep reinforcement learning) for patient-specific computational modeling and simulations is required, as proven by strong publication record

·        Deep knowledge and practical expertise in data fusion, inverse problem, optimization and probabilistic reasoning

·        Medical and human physiology knowledge is a plus

·        Hands-on experience with bio-sensors is a plus

·        Very strong coding skills and proven ability to quickly prototype research ideas in C++ are required. Further experience in Python and GPU programming is a plus

·        Outstanding written and verbal communication skills in English are required

·        Excellent interpersonal skills, with proven can-do and collaborative attitude, who is willing to accept challenges and responsibilities

·        Adaptability to work and collaborate in a growing, fast-paced and multi-disciplinary team

 

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