Student Thesis in Computer Science (f/m/x) - Exploring Visual Analytics in Wildfire Decision Support
DLR · Braunschweig
Part-time · Posted on 29 October 2026
Apply on the original siteOpen in FullTime with Benefits
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Student Thesis in Computer Science (f/m/x) - Exploring Visual Analytics in Wildfire Decision Support
Job Description
Req ID: 5317
Place of work: Braunschweig
Starting date: Zum nächstmöglichem Zeitpunkt
Career level: Student research project and final thesis
Type of employment: Part time, Full-time
Duration of contract: bis zu 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 our 12,000 employees 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!
The DLR Institute of Software Technology sees software as a catalyst for research and innovation. The institute's staff, currently numbering around 200, make a significant contribution to advancements in the fields of aviation, space, energy, transportation, and security through the development of state-of-the-art software solutions and innovative research.
Our areas of competence include reliable and safety-critical software systems, artificial intelligence, high-performance computing and quantum computing, human-system interaction and visualisation, software and systems engineering as well as digital platforms and digital twins.
What to expect
This thesis will explore current approaches to wildfire decision support systems (DSSs) with a focus on how analytical results are presented and used in decision-making contexts. While advances in wildfire modeling and geospatial analysis have significantly improved data availability, challenges remain in effectively communicating this information to end users. The project surveys existing wildfire DSS tools and related literature to identify common design patterns, limitations, and open challenges. Particular attention is given to the role of visualization and visual analytics in supporting interpretation, collaboration, and trust in DSS outputs. Based on these findings, the research investigates opportunities where concepts from the visualization research community may enhance current practices. The outcomes of this work may include a structured analysis of existing tools, design considerations, or exploratory visualization concepts to inform future wildfire decision support systems.
Your tasks
Literature review of existing wildfire decision support systems and their use in practice
Analysis of current visualization and interaction approaches used in wildfire decision support
Identification of common challenges and limitations related to interpretation, usability, and collaborative decision making
Examination of how uncertainty, temporal dynamics, and multiple scenarios are communicated in existing systems
Exploration of opportunities informed by research in visualization and visual analytics
Conceptual design or exploratory implementation of selected visualization approaches for wildfire decision support
Reflection on findings to derive design implications and preliminary guidelines
Your profile
You are studying in Computer Science, Mathematics, Data Science, Disaster Management or similar courses.
You own good knowledge in programming and particularly in visualization packages.
Knowledge of GIS-Tools is desirable.
And you are a team player with creativity, independence and personal responsibility.
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 5317) please contact:
Apoorva Karagappa
Apply now
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Original posting: jobs.dlr.de