Master Thesis: Simulation-Based Reinforcement Learning for Wire Arc Additive Manufacturing gesucht

vor 2 Wochen


Munich, Deutschland Siemens AG Vollzeit
Mode of Employment:

Limited Develop what will be important tomorrow. Do you like the sound of finding the smartest solution side by side with professionals and experts? If so, complete your bachelor's or master's thesis with us. We can help you to combine knowledge, discover connections, and formulate ideas. When you join our team, you will gain an insight into a range of departments and processes. It is a chance like no other to break new ground as we head into the future of electrification, automation, and digitalization. Seize this opportunity today Change the future with us. You will develop a physics-based simulation environment for a Wire Arc Additive Manufacturing process You will select an appropriate Reinforcement Learning algorithm for simulation-based optimization, considering factors such as exploration-exploitation trade-off and sample efficiency You will integrate the RL agent within the simulation environment Your tasks include conceptual design and implementation in Python or Matlab/Simulink of the control system You will analyze data recorded by the monitoring system to validate the simulation-based RL control system approach The duration of the Master's Thesis is based on university regulations What you need to make real what matters. You are currently enrolled in a Master's degree program in computer science, engineering, mechatronics, robotics, physics or a related subject You have experience in simulation tools like ANSYS or Simufact You have experience in a programming language like Python Have some experience in Reinforcement Learning Good knowledge of additive manufacturing and git is an advantage Personally, you impress us with a high level of initiative, analytical thinking as well as a structured way of working in a team environment You have good English and/or German skills We've got quite a lot to offer. How about you?

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