Job Details

Job Title

Developer or Researcher – 5G-based UAV Traffic Management & Control

Job Duration

Initial contract is for 12 months, extensible based on performance.

Job Starting date

As early as possible.

Job Background

5G is touted as the generation of mobile networks that will support dedicated use-cases and provide specific types of services to satisfy simultaneously various customer demands. A recent study expects that the 5G mobile system should handle 100 times data traffic comparing to the circulated data traffic nowadays. Unlike the “one-fit-all” type of 4G architecture, 5G is anticipated to consider diverse business demands with often-conflicting requirements. One important use-case of the 5G system is Ultra-Reliable Low-Latency Communications (URLLC) that require ultra-low latency and very high reliability. One important application of URLLC is the beyond line of sight (BLOS) control of unmanned aerial vehicles (UAVs), whereby UAVs and their on-board Internet of Things (IoT) devices would be controlled remotely beyond line of sight by leveraging cellular networks and multi-access edge computing (MEC). URLLC use cases require high reliability, with a block error rate (i.e., BLER) lower than 10-9, and a low latency between 1-10 ms. 5G system should be also optimized to support the requirements of UAV services by taking into account the amount of traffic generated by the on-board IoT devices and the remote control of UAVs. Artificial intelligence (AI), such as deep neural networks and reinforcement learning techniques, would be widely used for processing the sensed data and making the decisions about the placement of different UAV controllers at the cloud and MECs. For this reason, AI, MEC and 5G will play a crucial role in enabling URLLC use-cases, particularly BLOS management of UAVs.

Job Requirements

We are looking for highly-motivated developers, young researchers and experienced postdoc researchers who are willing to conduct high-quality research works, developing efficient approaches and methods that leverage artificial intelligence, MEC and 5G technologies (e.g., network slicing, network function virtualization (NFV) and software-defined networking (SDN)) for providing efficient UAV management system. Depending on the job level, candidates should have either Master or Ph.D. degrees in a related field with a focus on artificial intelligence, cloud computing, and networking and communications. We expect that candidates should have good analytical skills including, but not limited to, optimization, artificial intelligence and queuing theories. We expect that the candidates have expertise in programming languages (Python, C/C++, Java), cloud environments (Kubernetes, OpenStack), open source tools (Apache libcloud, Open Source Mano, K8s and Jenkins), and different SDN technologies (e.g., opendaylight and ONOS). For the candidates applying for postdoc positions, they should have a good publications record in very good journals and conferences.

Research Group

The MOSA!C Lab is led by Prof. Tarik Taleb. The lab belongs to the Communications and Networking Department, School of Electrical Engineering, Aalto University. It consists of a group of highly-enthusiastic researchers with strong hands-on programming skills and expertise in different areas relevant to mobile networking, cloud computing, Internet of Things, and UAV. The lab is involved in a number of research projects funded by different industries, Business Finland, The European Commission, and Academy of Finland. MOSA!C Lab conducts high-quality research with high industrial applicability and contributes to open source projects.

How to Apply

The evaluation of the applications will start immediately and will continue until the positions are filled. Interested applicants should fill-in the form below and attach the following documents (pdf files only). Please note that incomplete applications will not be regarded.

  • Motivation letter.
  • Research vision on the topic.
  • Detailed CV including the list of publications, developed tools and softwares.
  • At least 3 recommendation letters.

Application Form

Full Name

 

Email Address

 

Short Bio

 

Curriculum Vitae

 

Motivation letter

 

Research Vision on the Topic

 

Recommendation Letters (merge at least three recommendations in one pdf file)

 
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