Data Scientist Generative Desi...

Siemens Siemens

Division Corporate Core Job Type Regular Business Unit Corporate Technology Job Time Full-Time Functional Area RD – Research & Development Experience Level Mid Level Req ID 151033 Required Education Masters Degree Location NJ – Princeton Required Travel 10%

Division Description

Siemens is a global technology powerhouse that has stood for engineering excellence, innovation, quality, reliability and internationally 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.

Our support functions are split into two organizations, Corporate Core and Corporate Services. These organizations provide essential services to better enable responsible and profitable growth.

For more information, please visit: http://www.siemens.com/businesses/us/en/

Job Description

For nearly 170 years, pioneering technologies and the business models developed from them have been the foundation of Siemens‘ success. Our central research and development unit, Corporate Technology (CT) plays an important role in this. Together with our global network of experts, we are a strategic partner to Siemens’ operative units and provide important services along the entire value chain – from research and development to production and quality assurance, as well as optimized business processes. Our support provided to the businesses in their research and development activities is ideally balanced with our own future-oriented research.

We at Corporate Technology are more than employees: We are actively helping to make people’s lives a little better every day. Would you like to be a part of that? Then join us. We offer you a high level of practical relevance as well as an opportunity to individually contribute your knowledge and your visions around the world. Whether you’re helping to develop products for the operating units or working in interdisciplinary projects for the business areas: At Corporate Technology you’ll be working in the heart of Siemens’ technological research together with the best.

We are currently seeking a Research Scientist Generative Design – Deep Learning for our Princeton, NJ location.

What are my responsibilities?

  • Lead the research activities focused at applying combination of Deep Learning and Knowledge Representation pipelines to design, analysis and engineering workflows for real world problems.
  • Research, design, and implement algorithms that power knowledge inference and online recommendations, based on Deep Learning, to consume design and engineering data in real-time.
  • Dive into huge, noisy, and complex real-world behavioral data to produce innovative analysis and new types of predictive models of engineering behaviors and manufacturing processes performance.
  • Advance the state-of-the-art in the field, including generating patents and publications in top journals and conferences.
  • Working with customers to understand algorithm requirements and deliver high-quality solutions.

Qualifications:

  • PhD required in Machine Learning or related field.
  • 7+ plus years of related experience.
  • Applied experience with anyone or more of Natural Language Processing and Deep Learning tools is a must. Skills in optimization, probabilistic reasoning, uncertainty quantification and design analysis are a plus.
  • Hands-on coding skills and ability to quickly prototype in C++ is a must. Further experience in one or more of following: R, WEKA, Pandas, Octave, Matlab, Python, Java, JavaScript.
  • Contribution to research communities and/or efforts, including publishing papers at conferences such at CVPR, ICCV, ACL, EMNLP, TACL, ICML or NIPS, etc.
  • Outstanding written and verbal communication skills in English are required in combination with excellent analytical and interpersonal skills and can do attitude.
  • 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

What else do I need to know?

For more information please refer to our website at www.usa.siemens.com

  • LI-JMA

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, national origin, citizenship status, ancestry, sex, age, disability status, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, protected veteran or military status, and other categories protected by federal, state or local law.

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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