Intern - AI/Deep Learning for Predictive Analytics
Business Unit: Corporate Technology
Requisition Number: 231742
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
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 an 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.
Posting Title: Summer Intern: AI/Deep Learning for Predictive Analytics
Are you interested in driving the revolution from automated to autonomous systems in real industrial applications?
Here’s the right internship opportunity for You!
Join our research group located in Princeton, NJ, for a summer internship starting in May 2019, and in research for predictive and prescriptive analytics. Our close contact to different business units in Siemens provides the opportunity to contribute to and gain experience in real industrial applications. During this internship, you will experience the excitement and challenges of industrial research.
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.
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.
What are my responsibilities?
- Conduct research in the area of predictive and prescriptive analytics
- Develop research prototypes as appropriate
- Generate technical reports as appropriate
- MS or PhD students in Operations Research, Computer Science, Electrical Engineering, Mechanical Engineering, or related discipline
- Excellent interpersonal skills and a can-do attitude
- Demonstrated ability working with python or another programming language
- Experience with Deep Learning tools such as Tensor flow, Theano, Torch etc.
- Capability for quick prototyping
- Past experience applying AI techniques to Mechanical Engineering and Materials Science problems would be a plus