PhD Early Stage Researcher in Artificial Intelligence for Management of 5G and Future Mobile Networks
Ericsson Research develops new communication solutions and standards. The organization has responsibility to provide Ericsson with world-class system concepts, technology innovations, and methodologies. The rapidly increasing demands for mobile broadband access in combination with needs for new technology and solutions for the digitalization of industries and societies creates challenging and exciting opportunities for our organization. Building on our experience from real network operations, profound knowledge about existing standards, and forward-looking research, we invent and master advanced concepts and solutions that shape today’s and tomorrow’s mobile radio communication.
We are looking for a smart, knowledgeable, and creative PhD student to strengthen our efforts in 5G network management, focusing on network control, orchestration and AI-driven automation.
Mobile communications networks are transforming with new 5G architectures and technologies introduced in the radio, core, and transport networks. Network Functions Virtualization (NFV) and Software Defined Networking (SDN) will be used for networking and programmability, bringing ultra-scalability, programmability and automation to the networks. Distributed cloud infrastructure platforms will be used for latency critical applications. A critical challenge in these networks is how to efficiently manage and orchestrate the combined resources end-to-end (radio, transport, core, cloud). The large scale complexity and the increasing operational dynamics emphasize the need for cross-domain automation and adaptability. Ericsson Research is addressing this challenge in the ongoing EU Innovative Training Network (MSCA-ITN) project called Spotlight (http://cordis.europa.eu/project/rcn/205539_en.html), where the objective is to create a fully-integrated and multi-disciplinary network of PhD student Early Stage Researchers (ESRs) that will analyze, design, and optimize the performance of new mobile network architectures.
Within the scope of the Spotlight project we are looking for an ESR to design and evaluate concepts for management of end-to-end resources (radio, transport, core, and cloud) in 5G and future mobile networks using machine intelligence techniques. The candidate will be temporarily employed by Ericsson Research and in the same time be a member of the ESR network in Spotlight project, participate of overall project meetings and meet other ESRs members. The employment is temporary and the selected ESR will be with Ericsson Research until end of 2020.
As the selected candidate will work toward her/his PhD degree and will have the chance to benefit from day-to-day interactions with world-class researchers and experts in mobile networks.
Be in the first four years (full-time equivalent research experience) of your research career
Not resided or carried out main activity in Sweden more than 1 year in the past 3 years
Not yet awarded a PhD degree
Highly driven with a curious mindset
Ability to formulate problems and solve them independently
Have good communication skills in written and spoken English
Excellent track record (university grades and/or prior research engagements)
Have completed the M.Sc. studies in Computer Science, Electrical Engineering or related field
Solid knowledge of Optimization techniques, Big Data analytics and Artificial Intelligence (AI) concepts and techniques such as Classification, Statistical learning, Neural networks, Deep learning, and Reinforcement learning.
Experience in reinforcement learning is a plus.
Good knowledge of computer networking technologies (e.g., TCP/IP) and programmable networking technologies like software defined networking (SDN) and network function virtualization (NFV)
Good knowledge of mobile communication network (3G, 4G and beyond) architectures and protocols
Hands-on experience in programming in languages like Python, C++, Matlab and R
Please submit your full application in English including the following material:
Research statement (Max. 3 pages)
Transcript of all university studies
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