This MSc programme explores quantum computing as a new computing paradigm that promises to accelerate extremely complex problem solving—from tasks that today take years down to minutes—and to tackle problems beyond the reach of conventional computers. It links quantum methods with data analytics to deepen understanding across scientific domains and trains students to apply quantum approaches in areas such as improved forecasting, cryptography, and drug development.
The curriculum is organised into four main module groups that collectively cover the full spectrum of quantum computing and related topics, giving students a broad and coherent foundation in both core theory and applied subjects. Taught in English in Cham, Germany, the programme sits within the field of computer science and is designed to prepare graduates for research roles, industry positions working on quantum algorithms and systems, or further study in advanced computing and interdisciplinary applications.
Typical prerequisites (confirm exact details on the official programme page)
Overview
This three‑semester Master’s programme is delivered on the Deggendorf campus within the Faculty of Computer Science and concludes with a research‑oriented Master’s thesis. The curriculum bridges high‑performance computing (HPC) and quantum computing (QC), combining theoretical foundations (physics, advanced mathematics) with practical, hands‑on modules (programming labs, technology and infrastructure). Students gain both the systems‑level view and low‑level scientific understanding needed for work in HPC/QC environments.
Key modules and learning outcomes
The first semester builds core knowledge: physics relevant to HPC/QC, software engineering practices, a dedicated HPC/QC programming laboratory, technology overviews, and advanced mathematics. The second semester moves to system and operational topics: computer architectures, networking, optimisation techniques, infrastructure, and system design and application of HPC/QC solutions, together with continued advanced mathematics and physics. The final semester is reserved for an elective, a master’s colloquium to present and defend research, and the master’s thesis.
Graduates will be able to:
Programme structure (module requirements)
Semester 1
Semester 2
Semester 3
Note: FWP I and FWP II are elective modules chosen in agreement with the study coordinator to tailor the programme to your interests.
Applicants should hold an undergraduate degree in a relevant scientific or technical discipline. Typical backgrounds include computer science, physics, or technology, though closely related subjects with strong quantitative and programming components are also appropriate. International applicants should ensure their bachelor’s degree is recognized as equivalent to the required qualification in Germany.
In addition to the degree, admission requires successful completion of the programme’s assessment test. Contact the admissions office or check the programme webpage for details on scheduling, format, and preparation materials for this test.
It’s a good idea to have transcripts and a clear description of your bachelor’s coursework available when applying, and to confirm any country-specific recognition or additional documentation needed well before deadlines.
Winter Semester (International)
1 October to 15 January for March entries (summer semester)
Summer Semester (International)
15 January 2027
Summer Semester (EU/EEA)
15 January 2027
Graduates are prepared for roles at the intersection of high-performance and quantum computing, such as quantum algorithm developer, HPC engineer, systems architect, or research scientist. The practical lab work and infrastructure focus equip students to design, implement and optimise computing systems for complex simulations and data-intensive applications.
Employment opportunities span research institutions and academia, tech industry (hardware and software vendors), finance, cryptography and cybersecurity firms, pharmaceutical companies (drug discovery and modelling), and startups working on quantum technologies. The degree also provides a foundation for doctoral studies in quantum computing and related disciplines.
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