Student Assistant (m/f/d) - Dynamic Charging Infrastructure

Dlr; Jena; Remote; EUR 10.000 - 12.000; Teilzeit

Zusammenfassung

DLR – Deutsches Zentrum für Luft- und Raumfahrt in Jena sucht eine/n studentische/n Hilfskraft (m/f/d) für das Projekt Dynamic Charging Infrastructure. Sie unterstützen die Weiterentwicklung des Power Forecast Mapper, verarbeiten dynamische Daten und beteiligen sich an der Verarbeitung von Nutzungskennzahlen der deutschlandweiten Ladeinfrastruktur.

Sie arbeiten im Team, verbinden Zeitreihen-Datenquellen mit Schnittstellen, führen Tests durch und dokumentieren Ergebnisse.

Qualifikationen

• Sie studieren derzeit im Masterstudium (M.Sc.) der Informatik oder eines vergleichbaren Fachs.
• Sehr gute Python-Kenntnisse.
• Erste praktische Erfahrung mit Time-Series-Datenbanken, ETL-Pipelines und Parallelisierung.
• Erfahrung mit push-basierten Datenströmen ist von Vorteil.
• Schnelle Auffassungsgabe, zielorientierte und eigenständige Arbeitsweise.
• Gute Deutsch- und Englischkenntnisse in Wort und Schrift.

Aufgaben

• Anpassung bestehender Implementierungen an neue Datenquellen im Rahmen der genannten Aufgaben.
• Anbindung einer Zeitreihen-Datenbank an mehrere Live-Daten-Schnittstellen zur Erfassung der Nutzung der deutschlandweiten Ladeinfrastruktur.
• Ableitung von Nutzungstrendlinien durch parallele Verarbeitung der erfassten Zeitreihendaten.
• Tests zur Pipeline-Stabilität und Fehlerbehandlung.

Kenntnisse

Python

Time-series databases

ETL pipelines

Parallelisation

Push-based streams

German & English

Ausbildung

Master in Informatik oder vergleichbar

Tools

Time-series databases

ETL pipelines

Parallelisation

Jobbeschreibung

Student Assistant (m/f/d) - Dynamic Charging Infrastructure Language Profile

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Student Assistant (m/f/d) - Dynamic Charging Infrastructure Job Description Req ID: 5826 Place of work: Jena Starting date: as soon as possible Career level: Student employment, Student research project and final thesis Type of employment: Part time Duration of contract: 6 Monate

Remuneration:

Remuneration is in accordance with the Collective Agreement for the Public Sector - Federal Government (TVöD-Bund).

Enter the fascinating world of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e. V.; DLR) and help shape the future through research and innovation! We offer an exciting and inspiring working environment driven by the expertise and curiosity of our12,000employees from 100 nations and our unique infrastructure. Together, we develop sustainable technologies and thus contribute to finding solutions to global challenges. Would you like to join us in addressing this major future challenge?Then this is your place!

At the Institute of Data Sciences 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 development into methods 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 Power Forecast Mapper (PFM) is a digital forecasting tool that determines future charging demand for electric vehicles, identifies suitable locations for new charging points and assesses their revenue potential. As part of the PFM2market transfer project, the PFM prototype that has been developed is being further refined for commercial use. Two student assistants are sought to map the existing charging infrastructure and its utilisation rates; the roles will have different areas of focus but will involve collaborative development. The focus here is on adapting existing methods and implementations to new data sources. This role focuses on processing dynamic data to derive utilisation metrics, whilst the other role involves the collection and preparation of static data (e.g. location & configuration; see vacancy 1234).

Applications as a team are expressly welcome: in this case, please apply individually for the respective position and state in your cover letter the name of the person with whom you are applying. Individual applications are, of course, also possible.

Your tasks

• Adapting existing implementations to new data sources as part of the following tasks:
• Connecting a time-series database to several live data interfaces to record the current utilisation of the Germany-wide charging infrastructure
• Deriving utilisation trend lines through parallel processing of the recorded time-series data
• Tests for pipeline stability and error handling

Your qualifications

• Currently studying for a Master’s degree (M.Sc.) in Computer Science or a comparable subject area
• Very good knowledge of Python
• Initial practical experience with time-series databases, ETL pipelines and parallelisation
• Experience with push-based data streams would be an advantage
• Quick learner with a goal-oriented and independent approach to work
• Good written and spoken German and English

We offer

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

We look forward to getting to know you!

If you have any questions about this position (Vacancy-ID 5826) please contact:

Dr. Friederike Klan
Tel.:[phone]

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