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  Re-advertisement: Semantic Communication for IoT Edge Analytics

   Graduate School of Technical Sciences

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  Assoc Prof Qi Zhang, Assoc Prof Panagiotis Karras  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

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 1 February 2023 or later.

Title: Re-advertisement: Semantic Communication for IoT Edge Analytics

Research area and project description:

The proliferation of the Internet of Things (IoT) and the ever-increasing massive IoT data provide unprecedented opportunities for innovations as well as pose challenges in data communication, storage and analytics. How to transmit massive amount of data from IoT devices to Edge/Cloud in real time, and how to extract knowledge and value from data have gained significant interest among researchers and industry. Conventionally, data communication and data analytics are designed and developed separately. Data communication following Shannon’s information theory focuses on designing compact bit representation of the data and reliable transmission. The emerging paradigm shift in data communication is from “semantic neutrality” towards semantic communication, which is trying to answer “how precisely do the transmitted data convey the desired meaning” and “how effectively does the received data affect machine intelligence to achieve a final goal, e.g., performing analytics and make a right decision”, instead of answering “how accurately can the data be transmitted”. Data analytics focuses on designing algorithms to perform fast and accurate data analytics, in particular, IoT analytics promises to realize proactive and predictive analytics by analyzing IoT data. The new trend is to perform IoT analytics at the network edge to significantly reduce the analytics response time and save the bandwidth to transport all the data to the cloud. However, the computation and storage capacity of edge computing is not comparable to that of cloud computing. Therefore, the question is not how to perform analytics on massive amount of IoT data, but rather how to perform analytics on the right data, furthermore, how the right data representation can facilitate and accelerate analytics.

In this project, we will jointly design sensor data representation, data transmission and edge analytics to address the technical challenges in the current IoT ecosystem.

  1. We will study the relationship between sensor data representation, data storage architecture, and data analytics, to understand their impact on communication efficiency, latency, accuracy, scalability, and fault tolerance.
  2. We will study existing data analytics methods so as to: (i) examine what extent they support IoT data analytics at Edge, and (ii) understand their performance tradeoffs and deficiencies.
  3. We will optimize the sensor data representation and compression not only for transmission but also for facilitating and accelerating data analytics.
  4. We will develop tailor-made techniques for IoT analytics at Edge, leveraging our previous expertise in data engineering.

Project description (2 – 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:

We are looking for highly motivated and independent students willing to take the challenge to do a successful 3-year PhD programme in Aarhus University. The ideal candidate will have the following profile (but not all items are required for a successful application):

  • Relevant Master’s degree (e.g., Computer Engineering, Computer Science, Software Engineering).
  • Excellent undergraduate and master degree grades are required.
  • Background on data communication, data analytics, machine learning, and data storage is highly desired, but candidates from other disciplines will be considered based on their merits and potential.
  • Background on mathematics, statistics and linear algebra is desired.
  • Strong programming skills in Python.
  • Good English verbal and written skills are required.

Place of employment and place of work:

The place of employment is Aarhus University, and the place of work is Department of Electrical and Computer Engineering, Helsingforsgade 10, 8200 Aarhus N., Denmark.


Applicants seeking further information are invited to contact:

How to apply:

Please follow this link to submit your application. Application deadline is 1 December 2022 at 23.59. Preferred starting date is 1 February 2023.

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

Please note:

  • 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.   

Computer Science (8) Mathematics (25)
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