We are seeking 10 highly motivated fellows eager to pursue a career in science, obtain a PhD abroad and work in SCION research project under the Doctoral Network (DN) Marie Skłodowska-Curie Actions (MSCA) call of the European Commission. The SCION focuses on the study of Secured and Intelligent Massive Machine-to-Machine Communications for 6G. Doctoral Candidates (DCs) will be supervised by researchers across the network, will be exposed to different sectors via planned placements, attend summer schools, and contribute to and organise workshops and conferences. DCs will be funded for 3 years and will pursue a doctoral degree during this time.

SCION Abstract  

To satisfy the expected plethora of demanding services, 6G is envisioned as a revolutionary paradigm to carry forward the capacities of enhanced broadband, massive access, and Ultra-reliable and low latency services in 5G wireless networks to a more robust and intelligent level. This move will introduce significant new multidisciplinary research challenges emerging throughout the wireless communication protocol stacks, including the way the mobile network is modelled and deployed. The structure of 6G networks will be highly heterogeneous, densely deployed, and dynamic. Combined with the tight quality of services, such complex architecture will result in the untenability of legacy network operation routines. In response, artificial intelligence (AI), especially machine learning (ML), Semantic Communication and Digital Twin (DT) are emerging as solutions to realize the fully intelligent network orchestration and management. By learning from uncertain and dynamic environments, AI-enabled channel estimation and spectrum management will open up opportunities for bringing the excellent performance of Ultra-broadband techniques into full play. Additionally, challenges brought by Ultra-massive access concerning energy and security can be mitigated by applying AI-based approaches. The overall research objective of the SCION project is to develop and design the network systems for seamless wireless access for Secure and Intelligent Massive Machine-to-Machine Communications for 6G. In addition to technology development, to meet the urgent needs for the future working force of the coming 6G era, this collaborative project will create a training network for Doctoral Candidates who will contribute to the design and implementation of future 6G networks.

For further information about SCION: https://cordis.europa.eu/project/id/101072375

DC Position 1:

DC1 will be recruited by University of ESSEX, United Kingdom. The thesis entitled Design of Semantic encoder and decoder is to design Semantic (Source) Encoder that detects and extracts semantic content (e.g., meaning) of the source signal and compresses or removes the irrelevant information. For further inquiries, please contact: leila.musavian@essex.ac.uk

For applicants to be considered for DC1, Please also check the local application at https://www.essex.ac.uk/jobs  for local arrangements and requirements.

DC Position 2:

DC2 will be recruited by University of ESSEX, United Kingdom. The thesis entitled Optimal power splitting for simultaneous power and information transfer to analyze the power splitting factor for achieving the overall communication performance of the machine-to-machine network and the implementation issues within the transceiver of the sensor nodes. For further inquiries, please contact: leila.musavian@essex.ac.uk

For applicants to be considered for DC1, Please also check the local application at https://www.essex.ac.uk/jobs  for local arrangements and requirements.

DC Position 3:

DC3 will be recruited by KTH, Sweden. The thesis entitled Joint optimized Shannon and Semantic encoder and decoder is to use semantic entropy for designing efficiency semantic encoder and decoder, which is defined based on the specific semantic communication scenario. For further inquiries, please contact: mingx@kth.se

The interesting applicants to DC3 should also apply following link: https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:593178/where:4/ 

DC Position 4:

DC4 will be recruited by KTH, Sweden. The thesis entitled Digital Twin modelling for M2M use case is to investigate the modelling of Virtual Entity, Phyical Entity, connection and service system for Machine to machine by using graph model. For further inquiries, please contact: mingx@kth.se

The interesting applicants to DC4 should also apply following link: https://www.kth.se/en/om/work-at-kth/lediga-jobb/what:job/jobID:593178/where:4/ 

DC Position 5:

DC5 will be recruited by Eindhoven University of Technology, Netherlands. The thesis entitled Efficient Reconfigurable Mechanisms for Fault Recovery to design an event-driven approach to classify different faults and to activate a cooperative communication based M2M connectivity recovery mechanism. For further inquiries, please contact: k.c.joshi@tue.nl

For applicants to be considered for DC5, you must also complete the local application at https://jobs.tue.nl by the same deadline.

DC Position 6:

DC6 will be recruited by Izmir Institute of Technology, Türkiye. The thesis entitled AoI approaches for Real-time Network Malfunction Forecast and Detection is to develop novel compression, pruning, and simplification methods to significantly decrease the complexity and size of Age of Information (AoI) models for the traffic between machines and the base station, exploiting the power of convolutional neural network. For further inquiries, please contact: bernaozbek@iyte.edu.tr

The qualified DC6 must fulfill the requirements at https://lee.iyte.edu.tr/en/graduate-application/applications-to-ph-d-pr…

DC Position 7:

DC7 will be recruited by Huawei, Germany. The thesis entitled Cyber-Physical System (CPS) Requirement Analysis and System Architecture Design is to design and develop a novel framework that allows the distribution of intelligence to optimize network functionalities from the physical to the application layer by AI/ML tools. For further inquiries, please contact: Xueli.An@huawei.com

DC Position 8:

DC8 will be recruited by Data Magnum Ltd., Portugal. The thesis entitled Blockchain modelling and optimization for Intelligent Digital Twin is to develop and implement a novel blockchain-based framework for Intelligent Digital Twin by ensuring transparency, decentralized data storage, data immutability, and machine-to-machine communication in industrial sectors. For further inquiries, please contact: francisco.ferrao@data-magnum.com

DC Position 9:

DC9 will be recruited by Data Magnum Ltd., Portugal. The thesis entitled Transfer learning to Forecast Faults based on Knowledge from Existing Network is to exploit the fault classification knowledge from the rich existing network management and develop a deep convolutional transfer learning-based method for fault classification.For further inquiries, please contact: francisco.ferrao@data-magnum.com

DC Position 10:

DC10 will be recruited by IRIS Automation Ltd., United Kingdom. The thesis entitled AI-based Intelligent center and decision modeling and optimization is to design AI-empowered 6G cellular network architecture in which an AI controller will act as an application on top of network operating or an independent network entity and communicate with RAN, core network, or global software defined network (SDN) controllers using open interfaces.. For further inquiries, please contact: r.iqbal@interactivecoventry.com

How to apply

Please send an email to scionproject@iyte.edu.tr by selecting a maximum of two DC positions and provide the following information (in English) in one single PDF file:

• Personal information, such as name, date of birth, nationality, and contact details.
• Detailed Curriculum vitae.
• Motivation letter (maximum 2 pages) highlighting your research experience and academic achievements and explaining why you are interested in SCION and the selected PhD thesis topics.
• A scanned copy of certified academic records. These documents must show the grades attained in exam periods, when applicable, and evidence that the required degree will be obtained by the expected time of recruitment if it has not already been awarded.
• Contact details of at least two referees from university lecturers or scientists who are familiar with your academic work and who can judge your potential as a predoctoral researcher.