Siemens Careers

Deep Learning and 3D Vision

Princeton, New Jersey
Research & Development

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English (US)

Job Description

Division: Siemens Healthineers
Business Unit: Strategy & Innovation
Requisition Number: 232937
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:

Deep Learning and 3D Vision

Job Description

The Medical Imaging Technology team of Siemens Healthcare Technology Center has an immediate opening in Princeton, NJ for a research scientist with a focus on Deep Learning and Computer Vision for Medical Applications. 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. Our team has a strong publication record in leading journals and conferences.

What are my responsibilities?

• Research, design, and implement algorithms in Deep Learning for Computer Vision and Medical Imaging problems.
• Advance the state-of-the-art , including generating patents and publications in top journals and conferences.
• Work on large-scale, real-world problems.
• Fast prototyping, feasibility studies, specification and implementation of image and video analysis product components.
• Work with customers to understand requirements and deliver solutions


What do I need to qualify for this job?

• 3-5+ years of experience (including Ph.D. study), with strong knowledge in medical image analysis and machine learning.
• Graduate research and internship experience in device tracking, real-time image analysis or application of computer vision to medical domain
• Experience in GPU programming and deploying DL prototypes for practical applications is a plus.
• Proven ability to develop new research ideas as demonstrated by a strong publication record and early developments to the level of working system prototypes.
• Knowledge in real-time analysis of medical image sequences is a plus.
• Hands-on coding skills and ability to quickly prototype in C++ is a must. Further experience in scripting languages such as Python is a plus.
• Outstanding written and verbal communication skills in English are required
• Excellent interpersonal skills and a can-do attitude
• Strong collaboration skills and ability to thrive in a fast-paced environment.
• Successful candidate must be able to work with controlled technology in accordance with US Export Control Law. US Export Control laws and applicable regulations govern the distribution of strategically important technology, services and information to foreign nationals and foreign countries. Siemens may require candidates under consideration for employment opportunities to submit information regarding citizenship status to allow the organization to comply with specific US Export Control laws and regulations. Additional information on the US Export Control laws & regulations can be found on http://www.bis.doc.gov/index.php/policy-guidance/deemed-exports/deemed-exports-faqs?view=category&id=33#subcat34

 

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