Student (m/f/d) - Physics, Computer Science, Mathematics

German Aerospace Center (DLR); Jena; Vor Ort; EUR 17.000 - 22.000; Teilzeit

Zusammenfassung

The Institute of Data Science at the German Aerospace Center (DLR) in Jena offers a student role focused on interactive software development and literature review in causal inference and time series analysis.

You will work up to 20 hours per week, applying Python, Plotly and ipywidgets to demonstrate concepts and present results in team settings.

Qualifikationen

• Enrolled student in computer science or a related field.
• Basic knowledge of programming concepts.
• Interest in Python and interactive software development.
• Proficient written and spoken English.

Aufgaben

• Develop interactive software for presentation purposes.
• Review literature on causal inference and implement concepts.
• Present results to the team and stakeholders.
• Code review and thorough documentation of work.

Kenntnisse

Programming basics

Python interest

English proficiency

Mathematics basics

Time management

Ausbildung

Computer science student

Tools

Plotly

ipywidgets

Jobbeschreibung

At the Institute of Data Science in Jena, we are working to make the data backbone for all of DLR’s areas of application (aviation, space, energy, transport, security) a reality. To this end, we conduct interdisciplinary research and method development with a focus on applications such as sustainable and circular processes, resilient supply chains, data-driven value chains and robust decision support. The methods developed in this way are put into practice in cooperation with other DLR institutes and external partners, whether as part of joint projects or through technology transfer activities.

What To Expect

The department Data Analysis and Intelligence develops and applies methods that enable the analysis of complex and large datasets. To this end, the department leverages techniques from machine learning and causal inference, as well as domain-specific process knowledge.

The research group “Causal Inference” has the scientific objective to contribute to a data-driven understanding of complex dynamical systems. To this end, the group develops and applies methods and software from the fields of causal inference and statistical learning. In doing so, the group follows an application-driven approach. In addition to closely collaborating with the users of the developed methods, this means to identify requirements that arise in applications and to address these requirements by further method development. The group has a special focus on time series data, and it also works on quantum machine learning.

As part of the student role, you will carry out your work duties for up to 20 hours per week.

Your tasks

• Development of an interactive software for presentation purposes
• Review of research literature on causal inference and implementation of the corresponding concepts and algorithms
• Presentation of the results
• Code review and documentation

Your Qualifications

• Currently studying computer science or a related subject
• Knowledge of the basic programming logic
• Basic knowledge in mathematics, in particular linear algebra
• Experience in any programming language and interest in Python
• Knowledge or interest in developing interactive software, for example using Plotly, iPyWidgets or similar tools
• Written and spoken English

We look forward to getting to know you!

If you have any questions about this position Vacancy-ID 6317 please contact:

Prof. Christian Thiel
Tel.: [phone]