Research Associate (f/m/d) - Use of Machine Learning in rolling bearing CFD simulations for electromobility

The Institute for Machine Elements and System Development (MSE) researches the fundamental structural and tribological behavior of machine elements and depicts this in experimentally validated model descriptions. These model descriptions are used to analyze and design the functional, loss and noise behavior of entire technical systems with a focus on the drive technology of wind turbines, mobile work machines and electric mobility. The result is computational and constructive designs of specific technical solutions including proof of the required system properties on large test benches. Extensive experience with such model-based solution finding through to the conception of configurable products enables the MSE to research and develop methods of Model Based Systems Engineering as a central element of future industrial product development processes.
The MSE's bearing technology department researches the tribological and structural behavior of the machine elements rolling bearings, freewheels and plain bearings and thus represents the link between basic research and the consideration at the system level. The focus of the application-oriented research is, for example, the use in drive systems of wind turbines and electric mobility. Thematic focuses here are the interdisciplinary description of damage mechanisms, model-based service life prediction (especially fatigue and wear) and early damage detection with innovative condition monitoring. Currently available tools such as complex simulation methods, machine learning and highly efficient computing clusters are used in combination to generate fundamental findings. Current cross-industry questions relating to the bearings of electromechanical drive trains are methodically investigated and answered by coupling experimental and theoretical work.

Your profile

• Above-average university degree (Master or equivalent) in mechanical engineering or a similar discipline
• Independent and self-responsible working style
• Structured approach to solving complex, interdisciplinary problems
• Willingness to familiarize yourself with new subject areas and to carry out both theoretical and experimental work
• Confident command of German and English
• Strong communication and teamwork skills
• Willingness to travel on business (national/international)
• Extensive knowledge of simulation methods in mechanical engineering (including CFD, CAD, FE and EHD) is an advantage
• Previous knowledge of Matlab is desired
• We also welcome applicants with industry experience who see a doctorate as the next step in their career

Your tasks

You will strengthen our team in the area of ​​bearing technology, rolling bearing group. You will work as part of a
cross-institutional cooperation between the FZG (Munich) and the MSE (Aachen) in a project
that focuses on the CFD simulation of lubricating oil flow in transmissions of electrically powered vehicles
. The aim is to develop CFD replacement models of the rolling bearings used in the transmissions by
using machine learning.
You will validate the CFD simulations required for this and the CFD replacement models developed through accompanying experiments on our rolling bearing test benches and on the
transmission test benches in Munich. Your tasks include:

• Participation in a cross-institutional research project with clear relevance for industry with both theoretical and experimental character
• CFD simulations of lubricating oil flow in rolling bearings
• Development of CFD replacement models of rolling bearings using machine learning
• Experimental validation of CFD simulations and CFD surrogate models
• Collaboration with international and national scientific and industrial partners
• Presentation and publication of project results at meetings of project committees as well as at national and international congresses and conferences
• Planning new research activities and, if desired, tasks in the university education of future engineers
• Promotion in the course of the research project

About Us

RWTH is certified as a family-friendly university.
RWTH offers a wide range of health, counseling and prevention services (e.g. university sports) as part of university health management. For employees covered by collective agreements and civil servants, there is an extensive range of continuing education courses and the opportunity to purchase a job ticket.
The job advertisement is aimed at all genders.
At RWTH Aachen University, we particularly want to promote the careers of women and are therefore happy to receive female applicants.
Women will be given preferential consideration if they have the same suitability, skills and professional performance, provided they are underrepresented in the organizational unit and provided that reasons relating to the person of a competitor do not outweigh them.
Applications from suitable severely disabled people are expressly welcome.
In the interests of equal treatment, we ask you not to include a photo in your application.
Information on the collection of personal data in accordance with Articles 13 and 14 of the General Data Protection Regulation (GDPR) can be found at https://www.rwth-aachen.de/dsgvo-information-bewerbung .

Further information

The position
is to be filled as soon as possible and is limited to one year.
An extension of two further years is planned.
The fixed-term employment is within the framework of the fixed-term employment options of the Academic Fixed-Term Contract Act.
This is a full-time position.
There is the possibility of a doctorate.
The classification is based on the TV-L.
The position is rated EG 13 TV-L.