PHD STIPENDS IN MACHINE LEARNING CONCEPTS FOR 6G AIR INTERFACE –-AALBORG UNIVERSITY-DENMARK

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  • Post Date: November 22, 2021
  • Apply Before: November 30, 2021
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Job Overview

ONE OR MORE PHD STIPENDS IN MACHINE LEARNING CONCEPTS FOR 6G AIR INTERFACE 

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At the Technical Faculty of IT and Design, Department of Electronic Systems, one or more PhD stipends in Machine Learning concepts for 6G air interface are available within the general study programme Wireless Communications. The stipends are open for appointment from February 1 2022, or soon as possible thereafter.  In electronics engineering, Aalborg University is known worldwide for its high academic quality and the societal relevance of its research programmes. The Department of Electronic Systems consists of more than 200 employees, of which about 40 % are international and about 90 are enrolled PhD students. The Department hosts 620 students. The Department’s excellent research infrastructures and facilities accentuate its global position in teaching and research. The Department’s research centres around communication, antennas, control systems, AI, sound, cybersecurity and robotics. The Department plays an active role in translating discoveries and results into practical applications with industrial partners and IPR. The Department provides teaching for several BSc and MSc programmes using a problem- and project-based learning model.

JOB DESCRIPTION

In wireless communication systems, machine learning (ML) techniques have been historically applied to high layer operations such as radio resource management and service slicing. In the advent of the coming 6th generation of mobile communications, however, the interest in the development of ML-enabled air interface and physical layer techniques has been drastically increased. It is conjectured that the application of deep and reinforcement learning methods can lead to systems that are highly efficient, robust to changes in the network and environment conditions, and able to self adapt with minimal human interaction and monitoring.

This PhD study will be run in close cooperation with Nokia Bell Labs, and aims at exploring the potential of ML solutions for the physical layer of future wireless systems. This may include solutions for multi-antenna systems, communication over harsh time and frequency dispersive channels, flexible waveforms, and optimized retransmission schemes. The main objective is to design techniques that overcome state-of-the art “hand-crafted” technologies in terms of spectral efficiency and/or complexity, paving the way to intelligent self-learned 6th Generation (6G) systems. Active dissemination of the research findings via international conferences and high-quality journals is expected. Also, the research outcome is expected to impact future standardization of novel 6G technologies.

The ideal candidate for the position should have a solid background in the following areas:

  • wireless communication systems, and in particular baseband processing mechanisms;
  • estimation theory and statistical signal processing;
  • ML algorithms such as multi-layer perceptrons, convolutional neural networks, recurrent neural networks, generative adversarial networks, reinforcement learning, etc.

The ideal candidate should be capable of autonomously conducting research in the above areas, and should combine strong analytical skills with an attitude towards practical implementation. In that respect, experience with Python, Tensorflow, Matlab, and C++ is highly appreciated.

The succesful candidate will be hosted at the Wireless Communication Networks (WCN) section, which specializes in teaching, research and innovation within the domain of wireless and wired communication and network technologies. The section features a dynamic and international environment, which aims at producing high-level academic research while maintaining a tight interplay with relevant industrial partners. The WCN section and its precursors have significantly contributed to the development of current and past mobile communication systems, spanning from 2G (GSM) to the current 5G systems.

You may obtain further information from Carles Navarro Manchón, Department of Electronic Systems, phone: 99408759, email: cnm@es.aau.dk , concerning the scientific aspects of the stipend.

PhD stipends are allocated to individuals who hold a Master’s degree. PhD stipends are normally for a period of 3 years. It is a prerequisite for allocation of the stipend that the candidate will be enrolled as a PhD student at the Technical Doctoral School of IT and Design in accordance with the regulations of Ministerial Order No. 1039 of August 27, 2013 on the PhD Programme at the Universities and Certain Higher Artistic Educational Institutions. According to the Ministerial Order, the progress of the PhD student shall be assessed at regular points in time.

Shortlisting will be applied. This means that subsequent to the deadline for applications the head of department supported by the chair of the assessment committee will select candidates for assessment. All applicants will be informed whether they will be assessed or not.

For further information about stipends and salary as well as practical issues concerning the application procedure contact Ms. Lisbeth Diinhoff , The Doctoral School at The Technical Faculty of IT and Design, email: ld@adm.aau.dk , phone: +45 9940 9589.

For more information of The Technical Doctoral School of IT and Design: www.phd.tech.aau.dk

The application is only to be submitted online by using the “Apply online” button below.

AAU wishes to reflect the diversity of society and welcomes applications from all qualified candidates regardless of personal background or belief.

AGREEMENT

Appointment and salary as a PhD fellow are according to the Ministry of Finance Circular of 28 June 2019 on the Collective Agreement for Academics in Denmark, Appendix 5, regarding PhD fellows, and with the current Circular of 11 December 2019 on the employment structure at Danish universities.

 

 

How to Apply

Job Detail
  • Offered SalaryNot Specified
  • Career LevelStudent
  • ExperienceNot Specified
  • GenderBoth
  • INDUSTRYEducation
  • QualificationMaster's Degree(M.Sc.)
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