You want to combine state of the art machine learning and data science methods with real world sensor data to help reducing aviation’s climate impact? At the Multiphase Flows and Alternative Fuels Department of the DLR Institute of Combustion Technology we got the right mission for you!

At the DLR Institute of Combustion Technology, we span the bridge from fundamental to applied sciences on research topics related to combustion and fuel. About 100 employees from various scientific fields utilize modern experimental and computing facilities, and diagnostics and numerical methods, to design and optimize clean combustion systems and to asses and optimize sustainable fuels. In the department of Multiphase Flow and Alternative Fuels (MAT) in Stuttgart, you will conduct and initiate projects in the field of alternative fuels for aviation, road transport, and the energy sector. Your research work will contribute to reducing, now, our impact on the environment and the climate.

In a team of about 10 scientists from Germany and abroad your research work ranges from the development of numerical methods and models, to the identification of promising fuel candidates using in-house computer codes and data science, to the coordination of flight tests aiming at characterizing the emissions of sustainable aviation fuels. One particular focus of the department is the holistic evaluation and optimization of fuels: fuel design. The aim is to explore possibilities for a climate-neutral use of fuels by means of digital methods. For this purpose, information and data must be collected and made available over the entire product life cycle. Since risk-related decisions are made on the basis of this information, uncertainties in data and models must be systematically recorded and evaluated. To facilitate this, a digital thread for representing process and information chains by means of digital twins for fuels shall be established within the scope of the position being advertised.

Within your mission, a hybrid sensor system for the fast online measurement of jet fuel properties (e.g. aromatic content, energy content) will be developed and its utilization at the airport and in fuel logistics will be demonstrated. This sensor system will combine sensor measurements and machine learning models and offers the potential to replace costly laboratory analytics. This could enable new potentials for reducing the climate impact of a flight mission, for example by adapting the flight routing to the available fuel or by optimized refueling strategies.