Working Student (f/m/d) Computer Science, Mathematics or Related Fields

Deutsches Zentrum für Luft- und Raumfahrt e.V. · Jena · up to 10 hours a week

WerkstudentGerman needed: not said

Still open on 1 Nov

You apply on the company's own website.

Key facts

Literature research on relevant scientific methods, algorithms, and papers for estimating wind direction from glider flight data, as well as anomaly detection, with the aim of critically evaluating new experimental and theoretical methods and deriving new approaches or solutions for your own work
Exploratory data analysis to evaluate data quality, completeness, consistency, and to identify potential data preprocessing steps
Development of robust workflows for data processing and analysis by parsing, cleaning, synchronizing, and transforming flight and sensor data
Analysis of datasets to identify patterns, trends, anomalies, and other relationships
Design, implementation, and iterative refinement of prototypical algorithms and analysis methods based on experimental results
Validation and testing of developed methods using available datasets, assessment of their accuracy and robustness
Documentation and presentation of results

Ongoing studies in computer science, mathematics, data science, or related fields
Solid programming skills in Python and relevant libraries such as NumPy, Pandas, SciPy, Matplotlib
Basic knowledge in data analysis, statistics, time series analysis
Interest in scientific research and the ability to conduct structured literature research and evaluate research papers
Initial experience with exploratory data analysis, data preprocessing, and visualization
Initial experience with development, testing, and documentation of scientific software or data analysis pipelines
Good English skills

DLR stands for diversity, appreciation, and equality for all people.
We promote independent work and the individual development of our employees in their personal and professional environment.
For this purpose, our numerous training and further education opportunities are available to you.
Equal opportunities are a particular concern for us; we therefore want to increase the proportion of women in science and leadership.
Applications from severely disabled persons are given preference in case of professional suitability.

Literature research on relevant scientific methods, algorithms, and papers for estimating wind direction from glider flight data, as well as anomaly detection, with the aim of critically evaluating new experimental and theoretical methods and deriving new approaches or solutions for your own work
Exploratory data analysis to evaluate data quality, completeness, consistency, and to identify potential data preprocessing steps
Development of robust workflows for data processing and analysis by parsing, cleaning, synchronizing, and transforming flight and sensor data
Analysis of datasets to identify patterns, trends, anomalies, and other relationships
Design, implementation, and iterative refinement of prototypical algorithms and analysis methods based on experimental results
Validation and testing of developed methods using available datasets, assessment of their accuracy and robustness
Documentation and presentation of results

Ongoing studies in computer science, mathematics, data science, or related fields
Solid programming skills in Python and relevant libraries such as NumPy, Pandas, SciPy, Matplotlib
Basic knowledge in data analysis, statistics, time series analysis
Interest in scientific research and the ability to conduct structured literature research and evaluate research papers
Initial experience with exploratory data analysis, data preprocessing, and visualization
Initial experience with development, testing, and documentation of scientific software or data analysis pipelines
Good English skills

DLR stands for diversity, appreciation, and equality for all people.
We promote independent work and the individual development of our employees in their personal and professional environment.
For this purpose, our numerous training and further education opportunities are available to you.
Equal opportunities are a particular concern for us; we therefore want to increase the proportion of women in science and leadership.
Applications from severely disabled persons are given preference in case of professional suitability.