43899: Data Scientist, Physicist, Mathematician, Geophysicist or similar - Condition monitoring and predictive maintenance of transport infrastructure

German Aerospace Center (DLR)

Berlin, Germany

Work group:

Institute of Transportation Systems



Area of research:

Scientific / postdoctoral posts



Job description:

Mobility has a high priority in our society. People want to reach their destination safely, comfortably and quickly. Goods must be transported cost-effectively over short and long distances. The consequences of mobility can be seen in environmental pollution, accidents and traffic jams, which increase with the ever-growing volume of traffic. These are the challenges we face at the Institute of Transportation Systems. We develop solutions for the safe and efficient mobility of the future.


Help us to shape the future of transport infrastructure! The DLR Institute of Transportation Systems is working together with practice partners on the development of the foundations for the predictive maintenance of road and rail infrastructures. Our goal is a resilient, highly available and trouble-free transport system with lower life-cycle costs. We are therefore conducting research into methods and algorithms for the detection, diagnosis and prognosis of facility conditions by means of measurement data from embedded sensors.


For this challenging work, our interdisciplinary Data Science team is seeking reinforcement in the areas of signal and data analysis, pattern recognition, machine learning and system modelling.


Your task is the analysis of measurement data, which provide information concerning the condition of selected systems and facilities of traffic infrastructure and vehicles. This includes not only pure data-driven analysis procedures but also the modelling of the investigated systems. The working collaboration will take place within the framework of national and international projects in cooperation with infrastructure operators, industry and other research institutions.



Please apply via recruiter’s website.

Quote Reference: 43899

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