Intern – Computer Vision and Medical Image Processing – Siemens – Princeton, NJ

Job ID: 5383
Job date: 2016-04-07
End Date:

Company : Siemens 

Country :

Role : Research Scientist 


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Job Description:
Division Healthcare (HC) Job Type Internship Business Unit SI - Strategy & Innovation Job Time Full-Time Functional Area RD - Research & Development Experience Level Entry Level Req ID 154060 Required Education Bachelors Degree Location NJ - Princeton Required Travel 0%
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, Healthcare and Financial Services.

The Siemens Healthcare Division 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. As a global leader in medical imaging, laboratory diagnostics, and healthcare information technology, we have a keen understanding of the entire patient care continuum-from prevention and early detection to diagnosis and treatment.

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

Job Description
The Medical Imaging Technology team of Siemens Healthcare Technology Center has openings in Princeton, NJ, for Research Scientists, Research Engineers, and Interns, with a focus on Computer Vision and Medical Image Processing. We create and deliver medical devices crucial for patient care. You will be encouraged to think out-of-the-box, innovate and find solutions to real-life problems. You will be able to witness your algorithms being used at hospitals world-wide. Our team has a strong publication record in leading journals and conferences. We are located ten minutes from the Princeton University campus, one hour from New York City and Philadelphia.

What are my responsibilities?

Research, design, and implement algorithms for Computer Vision and Medical Image Processing Advance the state-of-the-art, including generating patents and top publications Work on large-scale, real-world problems, be entrepreneurial in an environment that’s more startup than big company What do I need to qualify for this job?

Experienced in image processing. Strong background in at least two of the following fields: computer vision, pattern recognition, deep learning, bioinformatics, large-scale data analytics. Strong background in C++ and another language Education: Pursuing a degree in Masters and PhD in Engineering and Applied Math

Duration: 3 to 6 months

Siemens encourages qualified long-term unemployed individuals to apply for open positions.

Offer of employment with Siemens is conditioned upon the successful completion of a background check and drug screen, subject to applicable laws and regulations.

Equal Employment Opportunity Statement
Siemens is an Equal Opportunity and Affirmative Action Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, ancestry, national origin, sex, sexual orientation, gender identity, age, marital status, family responsibilities, pregnancy, genetic information, protected veteran or military status, other categories protected by federal, state, or local law, and regardless of whether the qualified applicants are individuals with disabilities.

EEO is the Law:
Applicants and employees are protected under Federal law from discrimination. Click here to learn more.

Pay Transparency Non-Discrimination Provision:
Siemens follows Executive Order 11246, including the Pay Transparency Nondiscrimination Provision. Click here to learn more.


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