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Qi Zhang

4 months ago

Postdoc Position: Edge AI for Goal-Oriented Semantic Communication Aarhus University in Denmark

Degree Level

Postdoc

Field of study

Computer Science

Funding

Available

Deadline

Expired

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Country

Denmark

University

Aarhus University

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Where to contact

Official Email

Keywords

Computer Science
Electrical Engineering
Information Technology
Deep Learning
Time Series Analysis
Wireless Communication
Energy Efficiency
Networking
Internet Of Things
Data Compression
6g Technology
Reasoning
Machine learning

About this position

This postdoctoral position at Aarhus University focuses on Edge AI for Goal-Oriented Semantic Communication, with a particular emphasis on developing semantic-aware communication systems for 6G networks. The successful candidate will join the Department of Electrical and Computer Engineering, working within the Communication, Control & Automation Section under the supervision of Professor Qi Zhang.

The research will involve semantic representation and reasoning on time-series data, designing and implementing Edge AI solutions for real-time analytics and decision-making, and creating energy-efficient, low-latency communication strategies. The position is part of the Nordic University Collaboration on Edge Intelligence (NUEI) project, funded by NordForsk, and offers opportunities to participate in seminars and co-supervise bachelor’s and master’s thesis projects. Applicants should have a PhD in computer engineering, electrical engineering, communication engineering, computer science, or a related field, with documented experience in deep learning (CNNs, Transformers), strong Python programming skills, and familiarity with deep learning frameworks such as PyTorch.

Experience with time-series data, Internet of Things, and wireless communication networks is essential, along with a strong publication record and excellent English communication skills. Additional experience with explainable AI and collaborative research environments is advantageous. Aarhus University provides a vibrant, inclusive research environment with access to state-of-the-art facilities, strong support for career development, and a commitment to diversity, equity, and work-life balance. Denmark offers excellent quality of life, family-friendly policies, and public services.

The position is full-time, fixed-term for one year starting February 1st, 2026, with the possibility of a one-year extension. Salary and employment conditions are in accordance with Danish university agreements. Applications must be submitted in English via the university’s recruitment system by November 24th, 2025, and should include all required documentation.

For further information, applicants may contact Professor Qi Zhang at [email protected].

Funding details

Available

What's required

Applicants must hold a PhD in computer engineering, electrical engineering, communication engineering, computer science, or a related field. Documented experience with deep learning techniques (such as CNNs and Transformers), strong programming skills in Python, and experience with deep learning frameworks (e.g., PyTorch) are required. Experience working with time-series data and a good understanding of Internet of Things and wireless communication networks and systems are essential. Candidates should have a strong publication record relative to their career stage and excellent written and spoken English communication skills. Additional advantages include experience with explainable AI methods and collaborative, cross-cultural research environments. Applications must be in English and include a CV, degree certificate, publication list, statement of future research plans, and information about research and teaching activities.

How to apply

Submit your application via Aarhus University's recruitment system using the provided application link. Ensure your application includes all required documents: CV, degree certificate, publication list, statement of future research plans, and information about research and teaching activities. Applications must be received by November 24th, 2025. If you wish to include a referee, provide their contact information during submission.

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