Siemens
vacanciesineu.com
Job Family: Internal Services
Req ID: 436882
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!
Our R&D department develops technologies for the future of predictive maintenance on an industrial scale. In our work, we create technology with purpose. Therefore, we innovate in the field of plant and control technology, process monitoring as well as in materials engineering.
Change the future with us.
-
The focus of your thesis will be on exploring generalization capabilities and transfer learning methods in the context of physics informed neural networks (PINNs) for tool condition monitoring in subtractive manufacturing
-
You will investigate and evaluate different transfer learning techniques to improve the accuracy and efficiency of the existing PINN-based tool condition monitoring method
-
Your research will involve developing and implementing a transfer learning-based application that leverages pre-trained models and knowledge from prior research to enhance the estimation of remaining useful life and fault classification of different tools
-
The application will be validated and tested in a manufacturing lab environment to assess its performance and potential for a real-world deployment in industrial settings
What you need to make real what matters.
-
You are currently enrolled in a technical or scientific degree such as computer science, games engineering or engineering sciences
-
You have good experience in programming (ideally C++ and/or Python)
-
It would be an advantage to have experience in machine learning applications
-
You enjoy scientific work and are characterized by a structured and independent way of working
-
Very good written and oral English or German skills are required
We’ve got quite a lot to offer. How about you?
www.siemens.de (https://www.siemens.com/de/de.html)
if you wish to find out more about Siemens before applying.
Do you have questions about the application? Here (https://new.siemens.com/de/de/unternehmen/jobs/faq.html) you will find answers to frequently asked questions.
If you have more questions please contact: www.siemens.de/fragenzurbewerbung
www.siemens.com/careers
if you would like to find out more about jobs & careers at Siemens.
As an equal-opportunity employer we are happy to consider applications from individuals with disabilities (https://new.siemens.com/de/de/unternehmen/jobs/arbeiten-bei-siemens/inklusion.html) .
Apply Now
To help us track our recruitment effort, please indicate in your cover/motivation letter where (vacanciesineu.com) you saw this job posting.