IPE 04-2023 Master Thesis or Internship: Development of a Cloud-based Scientific Visualization Framework for large-scale experiment data
Organisationseinheit
Institut für Prozessdatenverarbeitung und Elektronik (IPE)
Ihre Aufgaben
Scientific visualization enables researchers to transform complex and abstract data into visually comprehensible representations. Through various visualization techniques, scientists can identify patterns, trends, and anomalies that might be difficult to discern in raw data alone. This process helps in acquiring a deeper understanding of the underlying phenomena and can lead to new insights and hypotheses.
In this project, you will be part of an overarching project that is designing and implementing a cloud-based scientific visualization framework for large scale experiment data. The framework must process and visualize data using cloud resources. Notably, the visualization modules can be integrated into the existing data monitoring framework of the KATRIN experiment (Karlsruhe Tritium Neutrino Experiment). The primary goal of this project is to leverage the scalability and computational power of the cloud to enable real-time or near-real-time interactive visualization of large datasets, overcoming the limitations of traditional local rendering techniques. You will be involved in part of the key tasks shown below:
Key Tasks:
- Literature Review: Conduct an in-depth literature review to understand existing cloud-based rendering techniques, volume visualization algorithms, and cloud computing platforms. Identify the most suitable approaches to form the foundation of the new framework.
- System Design: Based on the insights gained from the literature review, design a robust and scalable cloud-based scientific visualization framework. Consider factors like data storage, data transfer, load balancing, and resource management.
- Integration of Rendering Algorithms: Incorporate state-of-the-art visualization algorithms into the framework to enable high-quality visualizations.
- Performance Optimization: Investigate and apply optimization techniques to ensure efficient rendering performance on cloud resources.
Testing and Evaluation: Thoroughly test the developed framework using various scientific datasets and evaluate its performance in terms of rendering speed, image quality, and scalability.
Eintrittstermin
by appointment
Ihre Qualifikation
- Familiarity with programming languages such as Python or C++
- Basic knowledge of computer graphics and visualization techniques
- Proficiency in cloud computing concepts and platforms (e.g., AWS, Azure, or Google Cloud) is advantageous but not mandatory
Contract duration
6 months
Contact person in line-management
For further information, please contact Dr. Nicholas Tan Jerome, e-mail: nicholas.tanjerome@kit.edu or Dr. Suren Chilingaryan, e-mail: suren.chilingaryan@kit.edu.
Bitte bewerben Sie sich online über den unten stehenden Button für die Ausschreibungsnummer IPE 04-2023.
Ausschreibungsnummer: IPE 04-2023
Bei gleicher Eignung werden anerkannt schwerbehinderte Menschen bevorzugt berücksichtigt.Kontakt
Bei allgemeinen Fragen zur Bewerbung:
Personalservice (PSE) - Personalbetreuung
Frau Carrasco Sanchez
Telefon: +49 721 608-42016,
Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen