Within DLR's Quantum Computing Initiative the Institute of Data Science starts a cooperation project with industry to study the potential of hybrid Quantum-High-Performance-Computing for a selected industry-relevant use case. The concrete goal is to develop, apply und evaluate a hybrid algorithm that combines elements of classical high-performance-computing and machine learning with so-called "quantum machine learning" for the purpose of anomaly detection and in combination with causal inference. To this end the project will also establish a hybrid computing infrastructure that combines classical computers with quantum computers or simulators.

For this project we are searching for a candidate with experience in high-performance-computing and experience or interest in quantum computing and machine learning. Considering the growing importance and enormous potential of quantum computing, this position offers an exceptional opportunity for qualification. In addition, the industry collaboration will give the opportunity to build a valuable network.

Your tasks include:

• literature review to follow the developments within the fields of quantum computing and high-performance-data-analytics (HPDA)
• implementation and scaling of an existing data analysis pipeline for anomaly detection in a classical HPDA-environment
• implementation of a hybrid quantum computing infrastructure by using appropriate software interfaces
• development, implementation and evaluation of hybrid algorithms for anomaly detection in telemetry data
• collaboration and coordination with other project members