Scientific activities / projects, PhD position

Data-Driven Assessment and Optimization of Sustainable Aviation Fuels

Starting date


Duration of contract

3 years


up to the German TVöD 13

Type of employment

Full-time (part-time possible)

Help make aviation more sustainable and climate-neutral. How? Quite simple: Join the Aviation Fuel Impact team at the Institute of Combustion Technology and do research in the field of sustainable aviation fuels!

Despite the progress in electric- and hydrogen-powered airplanes, there are currently no technological alternatives to liquid fuels, particularly for medium- and long-haul flights. Therefore, there is a growing focus on research and development of sustainable fuels as a way to reduce carbon emissions and promote a more sustainable future. Changes in the composition of aviation fuel can influence several aspects of aircraft performance, including fuel efficiency and emissions of pollutants such as carbon dioxide, nitrogen oxides, and particulate matter. For example, the use of sustainable aviation fuels, which are produced from renewable sources such as used cooking oil and agricultural waste, can significantly reduce the carbon footprint of aircraft operations while also improving air quality. The composition of aviation fuel can also impact the formation of contrails, which can have an effect on cloudiness and climate. Finally, changes in fuel composition can also affect the cost of fuel and airline operations, with high-performance fuels potentially providing significant cost savings. Therefore, on the one hand, there is a push to approve as many sustainable fuels as possible, while on the other hand, there is a need to ensure that the use of new fuels does not result in any risks.

To address this, sustainable aviation fuels (SAF) are being extensively researched at the DLR Institute of Combustion Technology. The institute is involved in a number of large European research projects, both in the field of fuel production and fuel use. The aim is to develop sustainable fuels with a particular focus on minimizing the impact on the climate to enable a world of tomorrow worth living in.

In the last few years, unique data sets on the effects of a wide variety of fuels have been collected in international ground and flight measurement campaigns. On this basis, our team in the department of Multiphase Flow and Alternative Fuels (MAT) develops and applies data-based methods (big data, machine learning, digital twin) to maximize the benefits of sustainable fuels. As part of the department, you will work in an international team of about 12 scientists from Germany and abroad.

Your mission will be the data-driven assessment and optimization of Sustainable Aviation Fuels with respect to aircraft performance, emissions and environmental impact.

You have the following tasks:

  • training und validation of probabilistic machine learning models
  • evaluation of the current predictive capabilities with respect to new fuel production routes and the influence of the distribution of the training data sets
  • identification of gaps in the fuel data and closing of those gaps by defining data points for the training of the ML models in collaboration with the DLR-VT analytics department
  • development of similarity metrics to identify risks and loss in accuracy, precision and reliability of the probabilistic ML models when being applied to novel fuel samples
  • evaluation of the potential of embedding general physical laws into the ML methodology
  • critical analysis and improvement of the methodology
  • tasks as part of the maintenance of the fuel data base
  • make specific data sets accessible via web-based dashboards
  • screening of fuel products with respect to present and future (100% SAF) approval standards
  • analysis and Identification of promising fuel candidates with respect to added values, e.g. minimize emissions and thus environmental impact
  • tasks as part of research projects
  • presentation and publication of (scientific) work results
  • There is the opportunity to do a PhD.
  • For qualified and motivated candidates, there is the possibility to graduate with a PhD degree from the University of Stuttgart.

Your qualifications:

  • completed Master’s degree (M. Sc. / university diploma) in engineering, e.g. aerospace engineering, process engineering or mechanical engineering, or computer science or physics, or the equivalent
  • collaborative team-player
  • adaptable, creative, motivated person, who loves learning
  • well-grounded in mathematics, i.e. calculus, linear algebra, probability and statistics
  • good command of written and spoken English
  • basic programming skills in Python
  • basic knowledge of data cleaning and transformations (ideally with pandas) as well as data visualization (ideally with matplotlib and plotly) is beneficial
  • basic knowledge of software development in a team (ideally with git) is beneficial
  • basic knowledge in Machine Learning algorithms (ideally with PyTorch) is beneficial
  • basic knowledge of working with NoSQL databases (ideally MongoDB) is beneficial
  • basic German language skills are beneficial

Your benefits:

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalleled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (f/m/x). Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.

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Technical contact

Dr. Georg Eckel
Institute of Cumbustion Technology

Phone: +49 711 6862-769

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Vacancy 81888

HR department Stuttgart

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DLR site Stuttgart

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DLR Institute of Combustion Technology

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