Internship Parking Utilization Index Students (f/m/d) of Transport Engineering, Computer Science or similar

Deutsches Zentrum für Luft- und Raumfahrt e.V. · Berlin

InternshipGerman needed: fluent

Still open on 12 Nov

You apply on the company's own website.

Key facts

Pay: Paid by public service collective agreement
Duration: 3 to 6 months; Fixed term 3 to 6 months
Language needed: German and English
Subject you study: Transport Engineering, Geoinformatics, Computer Science, Artificial Intelligence, Machine Learning

Development of a parking utilization index by combining traffic demand data from agent-based simulation models and real parking data (e.g., capacities, locations, usage patterns)
Iterative improvement of the index based on validation data and feedback
Application of AI models for automated derivation of parking utilization estimates and trend forecasts
Comprehensive documentation of the developed index, including methodology, results, and usage possibilities

Interest in transport topics and sustainable transport planning
Studies in transport engineering, geoinformatics, computer science, AI, machine learning or related fields
Experience with training and application of AI models
Knowledge in using transport simulation software such as MATSim and general concepts of transport modeling
Very good knowledge of data analysis with Python
Basic understanding of geographic information systems (GIS) in transport research
Very good German skills and 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 further training 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 management. Applications from severely disabled persons are given preference in case of professional suitability.

Development of a parking utilization index by combining traffic demand data from agent-based simulation models and real parking data (e.g., capacities, locations, usage patterns)
Iterative improvement of the index based on validation data and feedback
Application of AI models for automated derivation of parking utilization estimates and trend forecasts
Comprehensive documentation of the developed index, including methodology, results, and usage possibilities

Interest in transport topics and sustainable transport planning
Studies in transport engineering, geoinformatics, computer science, AI, machine learning or related fields
Experience with training and application of AI models
Knowledge in using transport simulation software such as MATSim and general concepts of transport modeling
Very good knowledge of data analysis with Python
Basic understanding of geographic information systems (GIS) in transport research
Very good German skills and 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 further training 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 management. Applications from severely disabled persons are given preference in case of professional suitability.