At the Institute of Data Science in Jena, we are working on making the data backbone a reality for all DLR application areas (aviation, space, energy, transportation, security). To this end, we develop and research methods in interdisciplinary work with a focus on applications such as sustainable and circular processes, resilient supply chains, data-driven value chains or robust decision support. The methods developed in this way are applied in cooperation with other DLR institutes and external partners, either as part of joint projects or as part of technology transfer activities.
What to expect
The research and development work of the department Data Analysis and Intelligence aims to generate knowledge from data and develop a deeper understanding of complex datasets and the associated processes. We develop data-driven approaches to gain insights and make informed.
The group "Process- and Knowledge-Based Data Exploration" has the scientific objective of creating a bridge between process knowledge and data analysis to promote data-driven decision-making. Their methods include the seamless integration of domain and process knowledge into data exploration, particularly through the analysis of time series data, the integration of physical models, and the development of image pattern recognition techniques. These approaches enable the extraction of practical insights with direct value for industries such as aviation, aerospace, and energy.
The position is established to advance scientific knowledge in the field of researching data-driven methods to complement physical numerical methods. This involves applied research.
Your tasks
- Designing new data-driven analysis methods to complement physics-based and numerical approaches (e.g., Empirical Mode Decomposition, Physics-informed Neural Networks).
- Planning new research projects in the field of data-driven data analysis.
- Developing and applying data-driven algorithms for the characterization of complex flows.
- Implementing and evaluating Empirical Mode Decomposition methods for time series analysis and interpolation of wind data.
- Adapting artificial intelligence algorithms in the field of image analysis for the automatic detection of flow changes in aviation.
- Preparing data according to the needs of stakeholders/project partners, including data formatting and metadata generation.
- Preparing project documentation and reports
Your profile
- Expertise in fluid mechanics, e.g. in the fields of meterorology, aerodynamics or sound analysis
- Research experience in the field of physical modelling
- Experience in the development of data-driven methods for signal analysis
- Experience in machine learning and artificial intelligence methods (deep learning and Physics-Informed Neural Networks - PINNs)
- Initial experience in the field of image processing
- Knowledge of and experience in the use of specialized software and programming languages such as Python and QGIS
We look forward to getting to know you!
If you have any questions about this position (Vacancy-ID 1778) please contact:
Clemence Dubois
Tel.: +49 3641 30960 190
