Staff Deep Learning Scientist - Whole Body Imaging

Siemens Healthineers
Location: 
Princeton, New Jersey
Job Type: 
Full Time
Closing Date: 
Friday, September 22, 2017

Division: Siemens Healthineers
Business Unit: Strategy & Innovation
Requisition Number: 211859
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:

Siemens is a global technology powerhouse that has stood for engineering excellence, innovation, quality, reliability and internationality for more than 165 years. As a global technology company, Siemens is rigorously leveraging the advantages that this setup provides. To tap business opportunities in both new and established markets, the Company is organized in nine Divisions: Power and Gas, Wind Power and Renewables, Energy Management, Building Technologies, Mobility, Digital Factory, Process Industries and Drives, Healthineers and Financial Services.

With 45,000 employees Siemens Healthineers is one of the world’s largest suppliers of technology to the healthcare industry and a leader in medical imaging, laboratory diagnostics and healthcare IT. All supported by a comprehensive portfolio of clinical consulting, training, and services available across the globe and tailored to customers’ needs. So that more people can have a life that is longer, richer, and more filled with happiness.

For more information, please visit:  http://www.usa.siemens.com/healthineers

Job Description:

Staff Research Scientist - Deep Learning - Medical Image Analysis

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 Medical Image Analytics. 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 Medical Image Analysis problems.

• Advance the state-of-the-art research, 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?

• Ph.D. in an engineering or science field such as Computer Science, Electrical Engineering, Statistics, or Applied Math

• Strong background in Deep Learning.

• 4+ years of industry experience or post-doctoral studies in Computer Vision, Machine Learning and Image Understanding preferred.

• Experience in GPU programming.

• 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-e...