Re-advertisement: Goal-oriented Semantic Communication for Internet of Things

4 weeks ago

Aarhus, Denmark Aarhus Universitet, Bygning 5125 Full time
Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position is available from 01 September 2024 or later. You can submit your application via the link under 'how to apply'.

Title:
Re-advertisement: Goal-oriented Semantic Communication for Internet of Things

Research area and project description:
The Internet of Things (IoT) has demonstrated its extensive use in various sectors and plays an important role in digitalization. However, with wide deployment of IoT, significant challenges have emerged in handling unprecedented volume and heterogeneous IoT data, including issues related to data collection, transmission, and processing. Over the past few decades, various data compression methods have been proposed to address these challenges, primarily concentrating on reducing data volume for transmission and storage.

The need for more efficient communication for supporting the emerging intelligent and resource-demanding services has driven paradigm shift, known as goal-oriented semantic communication. This marks a departure from traditional communication systems that are rooted in Shannon-theory and focus on bit-level reliable transmission and reconstruction accuracy. Instead, the emphasis is placed on semantic extraction to accomplish downstream tasks efficiently.

This project aims to holistically devise semantic extraction using deep learning in conjunction with the processing of various downstream tasks. The goal is to optimize communication efficiency while maintaining the accuracy of these downstream tasks. Additionally, the project will explore the ways in which goal-oriented semantic communication can enhance data security and privacy within the realm of IoT.

Project description (½-4 pages): This document should describe your ideas and research plans for this specific project. If you wish to, you can indicate an URL where further information can be found.

Qualifications and specific competences:
Master’s degree in Computer Engineering, Communication Engineering, Electrical Engineering, or within a relevant area.
Background on machine learning is required.Strong programming skills, especially Python programming, is required.Excellent English verbal and written skills.Background in deep learning, or wireless communications system is a plus.
Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Helsingforsgade 10, 8200 Aarhus N, Denmark.

Contacts:
Applicants seeking further information are invited to contact:
Associate Professor Qi Zhang, qz@ece.au.dk (main supervisor)Assistant Professor Hei Victor Cheng, hvc@ece.au.dk (co-supervisor)Professor Daniel Enrique Lucani Rötter, daniel.lucani@ece.au.dk (co-supervisor)
How to apply:
Please follow this link to submit your application.

Application deadline is 20 May 2024 at 23:59 CEST. Preferred starting date is 1 September 2024.

For information about application requirements and mandatory attachments, please see our application guide.

Please note:Only documents received prior to the application deadline will be evaluated. Thus, documents sent after deadline will not be taken into account.The programme committee may request further information or invite the applicant to attend an interview.Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.
Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background. Salary and terms of employment are in accordance with applicable collective agreement.

 

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