Student Assistant for applied Machine Learning in the »Quantum Computing« Team (all genders)

Location

Stuttgart

Remote

On-site

Employment type

Student Jobs

Experience

Entry Level

Field

Social Work & Pedagogy

Requirements at a glance

Enrolled student (Required)
Linear algebra (Required)
Machine learning (Required)
Python (Required)
PyTorch (Required)
English (Required)
German (Preferred)

RequiredPreferred

Today

City: Stuttgart Date: Oct 21, 2026

Student Assistant for applied Machine Learning in the »Quantum Computing« Team (all genders)

The Fraunhofer-Gesellschaft is one of the world's leading organizations for application-oriented research. 74 institutes develop pioneering technologies for our economy and society – more precisely: 30 000 people from technology, science, administration and IT. They know: Anyone who comes to Fraunhofer wants to and can make a difference. For themselves, for us and for the markets of today and tomorrow.

The »Quantum Computing« team in the Digital Business research area at Fraunhofer Institute for Industrial Engineering IAO works on national and international research and consulting projects aimed at harnessing the potential of quantum computing for industry and society. Together with the Fraunhofer Institute for Manufacturing Engineering and Automation IPA, the team operates flaQship, the Fraunhofer Lab for applied quantum computing Stuttgart-Heilbronn. In this context, the team coordinates the »Kompetenzzentrum Quantencomputing Baden-Württemberg« and co-leads the office of the state initiative QuantumBW, and it offers a broad portfolio of training courses, symposia, trade fair appearances and knowledge transfer formats for companies, students and the general public.

Within this environment, our research group investigates tensor network methods for anomaly detection, combining concepts from quantum computing with state-of-the-art machine learning techniques. We develop novel tensor-based approaches, including tensor density estimation and tensor learning, to efficiently model and analyze high-dimensional data.

To support this research, we are looking for a motivated Student Assistant who would like to contribute to cutting-edge work at the intersection of quantum computing, machine learning, and artificial intelligence. As part of an interdisciplinary team, you will support the development and evaluation of innovative algorithms and have the opportunity to contribute to scientific publications and research outcomes.