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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

One-year postdoctoral appointment with salary according to the applicable collective agreement; extension may be possible depending on available funding.

Deadline

Dec 15, 2026

Country flag

Country

Denmark

University

University of Southern Denmark

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Keywords

Computer Science
Electrical Engineering
Information Technology
Mathematics
Ensemble Learning
Statistics
Physics
ML

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About this position

The Institute of Mechanical and Electrical Engineering at the University of Southern Denmark invites applications for a one-year postdoctoral position in Intelligent Computing Architectures, centered on hardware-aware quantum machine learning. The project asks how hybrid quantum-classical learning systems behave under realistic hardware constraints, including noise, limited quantum resources, device connectivity, finite sampling, and classical computational overhead.

The postdoc will work on the design, simulation, training, and evaluation of hybrid learning models and will investigate approaches such as hardware-aware model design, quantum-classical ensemble learning, mixture-of-experts, resource-efficient learning methods, and automated architecture search. A key part of the work is to assess learning performance alongside resource usage and to compare results against suitable classical baselines.

The position is embedded in SDU Microelectronics, a growing section within SDU’s Faculty of Engineering that combines expertise in integrated circuits, semiconductor technologies, spintronics, photonics, advanced computing, and energy-efficient system architectures. The role offers an open, collaborative research environment with opportunities to connect quantum machine learning to AI accelerators and resource-aware computing.

The successful candidate will also contribute to collaboration with academic, industrial, and technology-development partners, and support research proposals, publications, technical documentation, and project reporting. The research is supervised by Assistant Professor Alberto Marchisio, with additional section leadership contact from Professor Farshad Moradi.

Funding details

One-year postdoctoral appointment with salary according to the applicable collective agreement; extension may be possible depending on available funding.

What's required

Applicants should hold a PhD in Computer Science, Computer Engineering, Electrical Engineering, Quantum Computing, Machine Learning, or a closely related field, completed within the last 6 years. Strong experience in quantum programming with frameworks such as Qiskit or PennyLane, including implementation and simulation of quantum circuits, and strong machine learning experience with model implementation, training, and evaluation are expected. Experience in quantum machine learning, hybrid quantum-classical models, noise-aware optimization, ensemble methods, or automated architecture search is an advantage. A strong research track record with peer-reviewed publications is required, and experience writing research proposals, funding applications, or project plans is highly desirable. Applicants must have very good collaboration skills and excellent verbal and written English, with the ability to communicate technical results to multidisciplinary and international partners.

How to apply

Read the SDU information on how to apply and prepare the required documents in English and PDF format. Upload the motivated application under Cover letter, the CV under Resume, and all other documents under Miscellaneous documents. Submit the application via the application link before the deadline.

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Professors

Assistant Professor at University of Southern Denmark

University Name
Country flag

Denmark

Research Interests

Statistics

Ensemble Learning

Ml

Electrical Engineering

Physics

Professor at University of Southern Denmark

University Name
Country flag

Denmark

Research Interests

Statistics

Computer Science

Electrical Engineering

Mathematics

Ml