Senior Research Scientist – Deep Learning for Software Engineering

Job Description

Organization: Corporate Technology
Business Unit: Research in Digitalization and Automation
Requisition Number: 244682
Primary Location: United States-North Carolina-Charlotte
Assignment Category: Full-time regular
Experience Level: Senior level
Education Required Level: Doctorate Degree
Travel Required: 10%

Job Description:

Are you ready to make a difference and create the Future of Automation?

 

Do you dream about radically changing information technology sector by integrating AI capabilities into Software and Services?

 

If your research interest revolves around the intersection of Machine Learning, Software Engineering and Data Modelling Techniques, let’s talk!

 

We are looking for a motivated Senior Research Scientist who would like to be part of a dynamic team in Charlotte, NC.

 

CT is seeking a member of its “Production Automation Engineering” Research Group of the vertical “Future of Automation” Technology Field embedded in the manufacturing and Energy Hub of Carolinas. In this research group, we shape the innovation road map towards the production automation and engineering tools of the future; in collaboration with technology startups, leading academic institutions and government agencies. We are a team of automation-enthusiasts, innovators, engineers and scientists with deep technical expertise who are passionate about disruptive technologies in the areas of Machine Learning, Simulation, Engineering, Control, and Optimization. Our deliverables enable the successful transformation of the technology trends in Automation & Control into the business of the future for a multitude of customer products and services.

 
Responsibility in detail:
  • Manage scientific projects including the definition and execution of the technology strategy focused in the fields that are intersection of Machine Learning, Optimization and Controls for Human-System Collaboration.
  • Calculate/assess risk factors of a project. Anticipate potential problems and demonstrate sophisticated reasoning skills as well as creative, innovative and resourceful approaches to developing solutions to complex problems.
  • Provide technical supervision to achieve project goals.
  • Lead, and collaborate with others, both within and outside Siemens, to develop successful research proposals for external funding that align with Siemens strategic direction.
  • Scout and evaluate new automation & control technologies in collaboration with leading academic institutions and government agencies, by working with Siemens Business Units.
  • Seek advocacy from appropriate Siemens business units on potential use cases.
  • Manage cutting-edge research projects with the best universities and professors in the US. Co-develop with top academic partners the Automation Systems of the Future.
  • Educate and transfer technologies to Siemens business units for product implementations.
  • Assist in project acquisition and project funding
 
What skills are needed to qualify for this position?
  • PhD required in computer science, engineering, or a related field with minimum 5 years of related experience
  • Experience in one or more of the following: Natural Language Processing, Deep Learning, Reinforcement Learning, model-based/model-free reinforcement learning strategies et cetra
  • Experience in C++/Java/C# programming and object-oriented design.
  • Experience in C++/Python and one or more machine learning tools (Caffe, Tensor Flow, Theano)
  • Knowledge about industrial IoT connectivity frameworks, such as DDS, OPC-UA and PLC/PAC programming (Siemens, ABB, GE, Modicon, TI, SEL) is preferred
  • Demonstrated real-world software development experience in automation engineering system development like scaling, optimization, distributed systems design et cetra will be preferred
  • Experience in JavaScript and web technologies preferred.
  • Outstanding written and verbal communication skills in English
  • Collaborates well in an international and multi-cultural team environment

 

 

 #LI-MD1

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