Phd Student: Motion Control and Predictive

vor 2 Wochen

Gilching, Deutschland ABB Vollzeit

**PhD Student: Motion Control and Predictive Maintenance (M/F/d) - Robotics**:
**Take your next career step at ABB with a global team that is energizing the transformation of society and industry to achieve a more productive, sustainable future. At ABB, we have the clear goal of driving diversity and inclusion across all dimensions: gender, LGBTQ+, abilities, ethnicity and generations. Together, we are embarking on a journey where each and every one of us, individually and collectively, welcomes and celebrates individual differences.**:
We have an opening for a PhD student at our site in Gilching. You will be working in close collaboration with our ABB R&D team in Gilching and Sweden, as well as the Chair of Applied Mechanics of the TU Munich. As an ABB employed R&D engineer, you will be working on a research interface to allow universities deeper access into our collaborative robot GoFa’s control system. For your PhD studies, you will be given the opportunity to use this access to do public research on novel predictive maintenance, condition monitoring and in-field calibration methods for collaborative robots. Your PhD will be supervised by Prof. Rixen from the Chair of Applied Mechanics - TUM, where you will be spending at least one day per week to contribute to the chair’s research and teaching activities. This is a unique opportunity to work on the interface between professional product development and on the edge research. Join our team nearby Munich in an area that boasts one of the world’s highest quality-of-life indices and shape your future in robotics with us.

**Your responsibilities**:

- Implement and support a research interface for the ABB collaborative robot family.
- Align requirements for the research interface between universities and the ABB motion control team.
- Research on novel predictive maintenance, condition monitoring and in-field calibration methods for collaborative robots.
- Publication of research results and presentation on conferences.
- Supervision of related student theses.
- Support the Chair of Applied Mechanics in teaching activities.

**Your background**:

- Outstanding Master’s degree in Mechatronics, Mechanical Engineering, Computer Science or comparable.
- Demonstrable programming skills in C/C++.
- Knowledge in modelling of complex mechatronic systems in Matlab/Simulink/Modelica or similar.
- Preferably experience in one or more of the following topics:

- Signal Processing, Sensor Fusion, Condition Monitoring, Predictive Maintenance, Multi Body Systems.
- Fluent command of English, preferably complemented by German language skills
- Excellent communication skills across borders and cultures.

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