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Alberto Marchisio
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Postdoctoral Position in Intelligent Computing Architectures: Hardware-Aware Quantum Machine Learning University of Southern Denmark in Denmark
Degree Level
Postdoc
Field of study
Computer Science
Funding
Available
Deadline
Dec 15, 2026
Country
Denmark
University
University of Southern Denmark
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About this position
Hardware-aware quantum machine learning for intelligent computing architectures
The University of Southern Denmark is offering a postdoctoral research position in SDU Microelectronics, within the Institute of Mechanical and Electrical Engineering. The project focuses on hardware-aware quantum machine learning and the design of hybrid quantum-classical learning systems that remain effective under realistic device constraints.
The successful postdoc will investigate how noise, limited quantum resources, device connectivity, finite sampling, and classical computational overhead influence learning performance and implementability. The research direction is intentionally platform-independent, allowing the appointee to shape a focused and achievable programme together with the supervisor according to their expertise and the project goals.
Research activities may include hardware-aware model design and training, quantum-classical ensemble learning, mixture-of-experts approaches, resource-efficient learning methods, and automated architecture search. The work combines model design, quantum programming, simulation, training, and reproducible experimental evaluation, with explicit comparison to classical baselines and assessment of computational resource demands.
The postdoc will join a growing and interdisciplinary environment in SDU Microelectronics, a section active in analog and digital IC design, spintronics, advanced computing, semiconductor technologies, and energy-efficient system architectures. The position also offers opportunities to connect with academic, industrial, and technology-development partners in Denmark and internationally, and to contribute to proposals, publications, technical documentation, and project reporting.
The research will be conducted under the supervision of Assistant Professor Alberto Marchisio, with additional contact and section leadership from Professor Farshad Moradi. The position is embedded in a collaborative research culture within the Faculty of Engineering at the University of Southern Denmark.
The role is a one-year postdoctoral appointment starting in March 2027, with the possibility of extension subject to available funding.
Funding details
Available
What's required
Applicants should hold a PhD in Computer Science, Computer Engineering, Electrical Engineering, Quantum Computing, Machine Learning, or a closely related field, with the degree completed within the last 6 years. Demonstrated experience in quantum programming using frameworks such as Qiskit or PennyLane, including implementation and simulation of quantum circuits, is expected. Applicants should also have demonstrated machine learning experience, strong programming skills, a strong research track record with peer-reviewed publications, and excellent verbal and written English. Experience in quantum machine learning, hybrid quantum-classical models, noise-aware optimization, ensemble methods, automated architecture search, research proposals, funding applications, or project plans is highly desirable.
How to apply
Read the SDU information on how to apply. Prepare the required application documents in English and PDF format, then upload the motivated application under Cover letter, the CV under Resume, and all other documents under Miscellaneous documents. Submit the application through the online portal before the deadline.
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Professors
Assistant Professor at University of Southern Denmark
Denmark
Research Interests
Statistics
Ensemble Learning
Ml
Electrical Engineering
Physics
Professor at University of Southern Denmark
Denmark
Research Interests
Statistics
Computer Science
Electrical Engineering
Mathematics
Ml
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.