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.
The Corporate Technology Simulation and Digital Twin is seeking an excellent Graphical Knowledge Reasoning Research Scientist for our Princeton, NJ location. The successful candidate will join our Product Design, Modeling and Simulation Research Group (PSM-US) to help revolutionize design, engineering and manufacturing processes across a wide range of exciting domains.
Our Princeton facility is recognized for providing a stimulating environment for highly talented and self-motivated professionals. You will have the opportunity to test your modeling and machine learning skills 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. Responsibilities:
- Research, design, and implement algorithms that construct and utilize knowledge graphs based on highly heterogeneous, large-volume streams of data.
- Actively participate in challenging research projects that apply probabilistic graphical models, knowledge representation, deep learning to design, analysis and engineering workflows.
- Advance the state-of-the-art in the field, including generating patents and publications in top journals and conferences.
- Work with customers to understand algorithm requirements and deliver high-quality solutions.
Required Education, Experience and Skills:
- PhD degree in Computer Science, Electrical Engineering, Operations Research, Applied Mathematics. PhD in knowledge representation and/or machine learning (Bayesian inference, deep learning) is ideal.
- 5+ years of experience is required. Will consider recent PhD graduates with appropriate graduate research/ internship experience
- Proficiency in graphical databases and linked data framework development, maintenance and mining (Allegrograph, Jena, Blazegraph, ArangoDB or similar).
- Applied experience with anyone or more of knowledge representation, knowledge graph construction and inference, Bayesian inference, probabilistic modelling and reasoning. Skills in natural language processing and deep learning are a plus.
- Outstanding written and verbal communication skills in English are required in combination with excellent analytical and interpersonal skills and can-do attitude.
- Contribution to research communities and/or efforts, including publishing papers at conferences such at NIPS, ICML, SIGRAPH, CVPR, ICCV, UAI, ACL, EMNLP, etc.
- Team player who can also be independent, prioritize work and thrives in a fast-paced dynamic environment.
Requisition Number: 223596