Research Engineer (PhD Student) Advanced Digital Methods to Increase Reliability of Critical Power Unit Components (m/f/d)
The operational safety, efficiency and emissions of large internal combustion engines (ICE) in power generation and transportation applications depend greatly on the reliable operation of critical power unit components such as hydrodynamic sliding bearings. To avoid out-of-spec function, catastrophic failure or unforeseen engine downtime, it is therefore vital to continuously assess the condition of the bearing and the associated lubricant. For the research area “Simulation-based Development”, we are therefore looking for a motivated and innovative PhD student to develop data-driven strategies for condition monitoring of sliding bearings in large ICEs, in particular by employing advanced methods from the field of artificial intelligence (AI) and its subfield machine learning (ML).
Responsibility
- Get familiar with the fundamentals of the bearing condition monitoring process
- Support in developing a comprehensive testing strategy for the experimental investigation of bearings in different environments by employing approaches such as design of experiments
- Support in generating a comprehensive database with help of the experimental investigations
- Identify and evaluate data-driven approaches which serve to establish bearing condition monitoring applications
- Analyze the data obtained and realize data-driven approaches for bearing condition monitoring
- Interact closely within the LEC’s research team and with key persons from industry project partners
- Communicate the project results in regular internal meetings and to project partners
- Disseminate the project results in the form of scientific publications and elaborate a doctoral thesis
Your profile
- Qualified degree (MSc) in computer/data science, statistics/mathematics, physics or similar
- Good analytical skills combined with problem-solving orientation
- Interest in AI and in particular in ML techniques
- Experience in data analysis using Python, R or similar
- Interpersonal skills with initiative and perseverance
- Collaborative work in a multidisciplinary team
- Not afraid of technical writing
- Fluent in English, German is a plus
Our offer
- Possibility to elaborate a PhD thesis within an
exciting research project
- Availability of outstanding research infrastructure
at the Graz University of Technology campus
- Excellent possibilities for further personal and professional development
- Full-time position with a monthly gross salary of
€ 3.578,80,-
- Option to work part-time from home
- Earliest starting date: As soon as possible
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The LEC supports equal opportunities and diversity. We are looking for dedicated and motivated individuals with research talent.
Contact:
Herlinde Kohlmaier
Email: career@lec.tugraz.at
