Job
- Level
- Experienced
- Job Field
- Data
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Jena
- Working Model
- Onsite
Job Summary
In this role, you develop methods for causal inference and statistical analysis of dynamic systems, implement algorithms in Python, and evaluate their performance on large datasets.
Job Technologies
Your role in the team
- In the DW-DAI department, methods are developed and applied that enable the analysis of complex and large datasets.
- This involves the use of machine learning methods, causal inference, and domain-specific process knowledge.
- The "Causal Inference" group aims to contribute to a data-driven understanding of complex dynamic processes.
- To this end, the group develops methods and software from the fields of causal inference and statistical learning and applies them.
- The group follows an application-driven approach.
- In addition to close collaboration with the users of the methods, this means identifying needs from the applications and addressing these needs through targeted further development of the methods.
- A special focus of the group is on time series data.
- Furthermore, the group is working in the field of quantum machine learning.
- Literature research aimed at critically evaluating methods and software from the fields of statistics, machine learning, and dynamic systems, and making them usable for one's own work (current state analysis).
- Development of concepts for the (further) development of algorithms for data-driven analysis of dynamic systems and root cause analysis, e.g., for root cause analysis.
- Implementation of the concepts through the development of the algorithm in Python software, as well as the application of the implemented algorithms to synthetically generated test datasets and/or real datasets.
- Evaluation of the performance of the algorithms through systematic analysis of the results obtained from applying the algorithms using appropriate metrics (e.g., sensitivity, specificity, computation time, etc.).
- Documentation of the implementation, applications, and evaluation of the algorithms' performance.
- Review of work results regarding patentability and, if applicable, (co-)work in the patent application process.
- Preparation of work results in the form of scientific contributions for submission to professional journals and/or scientific presentations for presentation at conferences, workshops, trade fairs, etc.
This text has been machine translated. Show original
Our expectations of you
Education
- Completed academic university degree (Master's / Diplom University) in Mathematics, Physics, Statistics, Computer Science, Data Science, or another relevant field of study for the position.
Qualifications
- Expertise in the fields of dynamic systems and statistical modeling.
- Excellent programming skills in Python.
- Excellent written and spoken English skills.
Experience
- Initial experience in handling research tasks, preferably with a focus on dynamic systems as well as statistical and causal modeling.
- Experience in the preparation of scientific publications.
This text has been machine translated. Show original
Benefits
Work-Life-Integration
Topics that you deal with on the job
Job Locations
This is your employer
Deutsches Zentrum für Luft- und Raumfahrt eV.
As one of the leading research centers in the field of aerospace in Germany, DLR offers its approximately 8,700 employees the unique diversity of topics in aviation, spaceflight, energy, traffic, security and digitalization.
Description
- Company Size
- 250+ Employees
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Agriculture, Silviculture
Employer reviews
by devworkplaces.com
Total
(1 Review)3.4
Career Growth
2.8Workingconditions
4.2Engineering
3.1Culture
3.5
Data-driven analysis of dynamic systems
- Location
- Jena
- Working Model
- Onsite
- Diversity
- Open for all genders
