The Systems Engineering team in Leuven is developing a new tool which uses machine learning and reasoning techniques to support the early design and operations of mechatronic systems. To further expand the control capabilities of this tool, Siemens Industry Software is searching for a researcher who can bring new expertise in control engineering and scientific computing. The focus of this work will be on machine learning methods for control.
The position is part of a multidisciplinary research team, which combines expertise in artificial intelligence, multi-physical simulation, model-based design, and formal methods. The candidate will be responsible for the definition and execution of collaborative research projects that relate to reinforcement learning for control. She/he will keep track of and develop new design methods and implement prototype software solutions to assess their relevance. In addition, the candidate will work out industrial use cases to demonstrate and validate new approaches, often in close contact with industrial end users. She/he will also write scientific papers and present their work at international conferences.
The research associated with this position balances between state-of-the-art (often premature) methods and immanent industrial needs. At the same time, it requires both understanding domain-specific solutions as well as abstraction and generalization. In this challenging setup, the candidate will support the tooling roadmap of the team, both conceptually and through scripting and dedicated implementation. She/he will interface with other tools in the Simcenter system simulation portfolio for performance evaluation. Finally, this position involves strong interaction with internal and external research partners, in international academia and industry.
- MSc degree in computer science, control engineering, physics/mathematics, or related. Having a PhD degree in one of these domains is a strong asset.
- 2 or more years of experience in machine learning / artificial intelligence methods. Affiliation with reinforcement learning is an additional asset.
- High interest in and good programming skills (e.g., Python, C++)
- Practical experience with multi-physical simulation and/or optimization software
- Clear interest in the automotive sector and/or aerospace sector
- Dedicated and creative mindset for solving complex problems, good communication skills
- Fluent in English
About the company:
Siemens Industry Software NV (SISW) is an engineering innovation company, with proven track record in the area of experimental, numerical and hybrid (mixed experimental-numerical) system modelling for noise, vibration, durability and dynamics, performing substantial in-house research on advanced methods and applications. SISW is part of the Siemens Digital Industries Software, a leading global provider of product lifecycle management (PLM) software and services with seven million licensed seats and more than 71,000 customers worldwide. Headquartered in Plano, Texas, Siemens Digital Industries Software collaborates with companies to deliver open solutions, helping them making smarter decisions that result in better products. For more information on Siemens Digital Industries Software products and services, visit https://www.sw.siemens.com.
Organization: Digital Industries
Company: Siemens Industry Software NV
Experience Level: Experienced Professional
Job Type: Full-time