Siemens PhD Intern - Design Optimization and Data Analytics in Princeton, New Jersey
PhD Intern - Design Optimization and Data Analytics
Locations:Princeton, New Jersey
Job Family: Research & Development
Division: Corporate Technology
Business Unit: Corporate Technology
Requisition Number: 201367
Primary Location: United States-New Jersey-Princeton
Assignment Category: Full-time temporary
Experience Level: Entry level
Education Required Level: Master's Degree
Travel Required: No
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, Healthineers 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/
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 its global network of experts, CT is a strategic partner to Siemens’ operative units. It provides important services along the entire value chain – from research and development to production and quality assurance, as well as optimized business processes. The support provided to the businesses in their research and development activities is ideally balanced with CT’s own future-oriented research.
Siemens’ central research and development arm sees itself as a strategic partner to the company’s businesses. It plays a key role in achieving and maintaining leading competitive positions in the fields of electrification and automation while at the same time helping Siemens fully tap into the growth field of digitalization.
The people who work at CT are more than employees. They 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 CT you’ll be working in the heart of Siemens’ technological research.
The CT Automation and Control Technology Field is seeking a highly motivated PhD student available for a 3-9 month internship for our Princeton, NJ location. The successful candidate will develop design, modeling and simulation technologies for real-world problems .
Our Princeton facility is recognized for providing a stimulating environment for highly talented and self-motivated students. 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.
Develop prototypes for design exploration and optimization using state-of-the-art methods,including data analytics.
Incubate innovative concepts and develop innovative concepts and their implementation and publication in journals or patents
Collaborate with colleagues to implement reusable, efficient and maintainable software component using main stream programming languages.
Required Knowledge/Skills, Education, and Experience
Current student majoring in a PhD program in Computer Science, Mechanical Engineering, or related backgrounds.growing, dynamic team.
Previous graduate research or internship experience preferred.
Hands-on coding skills and ability to quickly prototype in C++ and Python.
Experience with at least one machine learning tool, such as Matlab, Scikit, Theano, etc.
Prior experience in CAD, CAE, multi-disciplinary optimization.
Experience with machine learning and other data analytics techniques.
Solid theoretical knowledge of geometry representations in design.
Publications and research experiences in related fields.
Strong collaboration skills and ability to thrive in a fast-paced environment. Outstanding interpersonal and communication (verbal & written) skills in English.
Drive and motivation for career development and open to taking on challenges.
Team player who can also be independent, prioritize work and thrives in a fast-paced dynamic 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
Qualified Applicants must be legally authorized for employment in the United States. Qualified Applicants will not require employer sponsored work authorization now or in the future for employment in the United States.
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, physical or mental disability, 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. To learn more, Click here at https://www.dol.gov/ofccp/regs/compliance/posters/ofccpost.htm .
Pay Transparency Non-Discrimination Provision
Siemens follows Executive Order 11246, including the Pay Transparency Nondiscrimination Provision. To learn more, Click here at https://www.dol.gov/ofccp/pdf/pay-transp_formattedESQA508c.pdf .