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Postdoc in Machine Learning concepts for 6G air interface

Aalborg Universitet (AAU)

At the Technical Faculty of IT and Design, Department of Electronic Systems, a position as postdoc in Machine Learning concepts for 6G air interface is open for appointment from September 2020, or as soon as possible thereafter. The position is available for 24 months.In the area of 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 employs more than 200 staff, of which about 40% are international, and about 90 enrolled PhD students. The Department hosts 620 students. The Department's excellent research infrastructures and facilities accentuate its global position in teaching and research. Department research centres around communication, antennas, control systems, signal processing, cyber security and acoustics. The Department plays an active role in translating discoveries and results in practical applications with industrial partners and through IPR. Within its subject field, 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. A very recent research trend is the application of ML also to the lower layers of the communication stack, such as physical layer and medium access control. It is indeed believed that a successful application of ML concepts to the low layers can result in a remarkable breakthrough on the way wireless systems are conceived and designed.

This postdoc project will be run in close collaboration with Nokia Bell Labs, and aims at exploring the potential of ML solutions for physical layer and medium access control of future wireless systems. This includes solutions for multi-antenna systems, communication over harsh time and frequency dispersive channels, flexible waveforms, and optimized retransmission schemes. The main goal is to design solutions that are overcoming 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, etc.

The ideal candidate should be capable of autonomously conducting research in the above areas, and should combine good analytical skills with an attitude towards practical implementation. In that respect, experience with Matlab, C++, Python and Tensorflow 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 professional information from Professor Preben Mogensen, email: pm@es.aau.dk

For more information about the department

Qualification requirements:
Appointment as Postdoc presupposes scientific qualifications at PhD–level or similar scientific qualifications. The research potential of each applicant will be emphasized in the overall assessment. Appointment as a Postdoc cannot exceed a period of four years in total at Aalborg University.

The application must contain the following:

  • A motivated text wherein the reasons for applying, qualifications in relation to the position, and intentions and visions for the position are stated.
  • A current curriculum vitae.
  • Copies of relevant diplomas (Master of Science and PhD). On request you could be asked for an official English translation.
  • Scientific qualifications. A complete list of publications must be attached with an indication of the works the applicant wishes to be considered. You may attach up to 5 publications.
  • Dissemination qualifications, including participation on committees or boards, participation in organisations and the like.
  • Additional qualifications in relation to the position. References/recommendations.
  • Personal data.

The applications are only to be submitted online by using the "Apply online" button below. An assessment committee will assess all candidates.

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

For further information concerning the application procedure please contact Lisbeth Palmelund by mail est-st-hr@adm.aau.dk or phone (+45) 9940 7553. Information regarding guidelines, ministerial circular in force and procedures can be seen here

Employment is in accordance with the Ministerial Order on the Appointment of Academic Staff at Universities (the Appointment Order) and the Ministry of Finance's current Job Structure for Academic Staff at Universities. Employment and salary are in accordance with the collective agreement for state-employed academics.

Vacancy number

Deadline / Ansøgningsfrist
31 May 2020

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Aalborg Universitet (AAU)
Aalborg Universitet (AAU)
AAU’s uddannelser og forskning er problem- og projektbaseret og har fokus på det tværdisciplinære. Gennem samarbejde mellem forskere, studerende og offentlige og private virksomheder udbyder vi virkelighedsnære uddannelser og skaber forskningsresultater i verdensklasse.

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