Research Scientist – Knowledge Graphs & Machine Learning

Job Description

Organization: Corporate Technology
Business Unit: Research in Digitalization and Automation
Requisition Number: 245082
Primary Location: United States-New Jersey-Princeton
Assignment Category: Full-time regular
Experience Level: Mid level
Education Required Level: Doctorate Degree
Travel Required: 10%

Division 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.


Job Description:

 

SIEMENS Corporate Technology is looking for a talented Research Scientist with a focus on applying knowledge graphs, graph databases and machine learning to new areas in engineering, automation and robotics, who would like to join our Automation Engineering Software (AES-US) Research Group of the “Future of Automation” Technology Field, in the Tri-state area.

 

The Team

 

Our team is composed of makers, innovators, engineers and scientists with deep technical expertise, who are passionate about disruptive technologies in knowledge graphs and machine learning and applying these technologies in the areas of industrial automation, engineering, and simulation. Our deliverables enable the successful transformation of the technology trends into the business of the future for a multitude of customer products and services.

Experienced candidates in these areas with the skills and interest in applying their knowledge and introducing innovative technologies into Siemens products are encouraged to apply!

 

AES-US Mission

Our mission is to produce innovative engineering tools and methods to make engineering convenient and to require less technical expertise, efficiently and with confidence in the results.

 

 

The Location

Our team is located in the wonderful Princeton NJ, a university town packed with outstanding international talent that provide a unique feel to this true cultural gem in the state. The town has plenty of activities to offer, but for those looking for more, at just about 1-h drive we  have NYC or Philly! We have the best public schools in the country and all of the above glued together by a very active and welcoming community!


Responsibilities

  • Developing a multi-disciplinary line of research and translating research results into practical applications and prototypes
  • Scouting and evaluating new software technologies that can be used in industrial environments and critical infrastructure
  • Defining and leading research projects, including technical supervision of software engineers and interns

  • Seeking support from appropriate Siemens business units on potential use cases

  • Transferring research results to Siemens business units for product implementations

  • Advising management and business units on disruptive technologies related to Engineering

  • Developing successful research proposals for external funding that align with Siemens’ strategic direction in collaboration with leading academic institutions and government agencies

  • Generating high-quality invention disclosures and patent applications

  • Building up a network of collaboration partners in Siemens business units and in US universities

Required qualifications

  • Ph.D. in Computer Science or related discipline required. Strong background in Machine Learning and Knowledge Graphs.

  • 5+ years of related professional experience or industry internships

  • Proven ability to develop new research ideas as demonstrated by a strong publication record and early developments to the level of a working system prototype.

  • Strong theoretical and practical background in knowledge graphs, graph databases and machine learning. Previous experience in Natural Language Processing or Visual Question Answering (VQA) preferred.

  • Hands-on coding skills and ability to quickly prototype in C++ is a must. Further experience in Scripting languages such as Python is a plus.

  • Outstanding written and verbal communication skills in English are required.

  • Good communication and organization skills, with a logical approach to problem solving, good time management and task prioritization skills, with motivation to learn and use new technologies, work under uncertainty at fast pace, and ability to multitask and make key contributions to several projects

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 https://www.bis.doc.gov/index.php/policy-guidance/deemed-exports/deemed-exports-faqs

 

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