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Job description
We are seeking to recruit a Doctoral Candidate in the framework of the Marie Sklodowska-Curie Doctoral Network NEWTON funded by the European Commission. The recruited candidate will join the Wireless Networks Research Lab (WiNe) and become a member of the Doctoral Network in an international environment, working closely with senior experts who will supervise the PhD and collaborating with the rest of the Doctoral Network fellows.
The UOC is a fully accredited University, partly funded by the Regional Government of Catalonia, operating from Barcelona and serving over 40,000 students worldwide. It was established in 1994 and has received international awards in recognition of its educational model and the quality of its academic activity. The Doctoral Candidate will work in the UOC's Research Hub, located in the 22@ District of Barcelona, the technological district, home of many major company headquarters and universities.
NEWTON, is a newly launched Marie Skłodowska-Curie Innovative Doctoral Network (DN) aiming at proposing a revolutionary approach of a converged wireless-optical network architecture that makes reality an efficient 6G Cell-Free (CF)-based access network for high-density and high coverage deployments. NEWTON proposes a new 6G networking approach spanning the radio-edge, regional-edge, and network-management domains and aligned with major 5G/6G technology roadmaps worldwide: at the radio-edge, it introduces cell-free (CF) solutions based on O-RAN and AI to improve radio capacity while reducing energy consumption by up to 30% and cutting costs by a factor of 4 via distributed cascaded optical-hybrid processing, alongside neuromorphic schemes targeting an order-of-magnitude power reduction in multi-antenna installations, a 10 dB BER improvement, and a 3 dB increase in processing-unit noise tolerance; at the regional-edge, it advances fronthaul support for CF radio units using multi-band XL-MIMO beamforming to double spectral efficiency versus mMIMO by leveraging context and array geometry, develops scalable Cloud Edge Continuum interconnection of data centers to at least halve SLA-violation correction time and SLA violation levels, and defines a converged wireless-optical design using TWDM-PONs to boost both spectral and energy efficiency by 2× in uplink and 3× in downlink; finally, at the network-management level, it delivers AI/ML-driven, multi-objective, user-centric orchestration for CF-mMIMO to improve overall energy efficiency by 20%, a decentralized compute-orchestration framework improving prediction accuracy by at least 25%, and joint management of radio, optical, and compute resources in multi-tenant environments to increase utilization by up to 20% through smart slicing.
In this context, NEWTON will build a training network to conduct top-notch research towards the development and experimental evaluation of a gamut of techniques, methodological frameworks, and tools.
The Doctoral Network also includes the following partners: IQUADRAT (coordinator), the KATHOLIEKE UNIVERSITEIT LEUVEN (KUL), ISRD SP Z O.O. (ISRD), EUR-EURECOM GIE, UNIVERSITY OF WEST ATTICA (UWA), NVIDIA DENMARK APS (NVIDIA), and RANPLAN WIRELESS NETWORK DESIGN LTD (RAN).
This research position targets the development of scalable, self-organizing solutions for the efficient management of computing infrastructure based on the Cloud-Edge Continuum (CEC) concept. As 6G networks evolve, managing the complexity of distributed computational resources requires a shift from centralized management to decentralized intelligence. The primary aim is to significantly improve network resilience and efficiency, specifically targeting a reduction in the time to correct network configurations when SLA (Service Level Agreement) is violated, as well as reducing the overall network SLA violation frequency.
The position focuses on a combination of swarm computing and decentralized intelligence where a swarm of nodes learns graph dependencies by effectively integrating the structure of distributed systems into neural network architecture. This approach extends Graph Neural Networks (GNNs) to model distributed systems while accounting for the high heterogeneity of devices in terms of storage, processing capacities, and specific hardware characteristics. The core of the methodology involves building an analytics framework for the modeling and prediction of application metrics in the CEC, where node attributes such as workload characteristics and network throughput change dynamically. This research specifically addresses the challenge of determining adjacency matrices in large-scale networks to learn the CEC connectivity precisely. By utilizing the adjacency matrix within GNNs, the framework offers modeling, interpretability, and the intelligent selection of swarms for a collaborative AI approach. The ultimate goal is to provide a spatio-temporal modeling and prediction framework that enables the autonomous self-configuration of swarm computing within the 6G infrastructure, ensuring high availability and SLA compliance through continuous, data-driven optimization.
Responsibilities Within the framework of NEWTON, the recruited researcher will work on his/her individual project entitled "Inter-computing self-organization of computing infrastructure in 6G networks", focused on the spatio-temporal modelling and prediction of the application metrics in the Cloud Edge Continuum for large-scale networks. The candidate is expected to do a secondment at NVIDIA (Denmark).
Requirements
Master Degree or equivalent, Master Degree or equivalent
Research Field Physics » Statistical physics
Education Level Master Degree or equivalent, * Must hold a Master in Electrical Engineering, Computer Science/Engineering, Math/Physics/Statistics or a related field.
- Have not yet been awarded a PhD degree.
- The Doctoral Candidate (DC) cannot already be in possession of a doctoral degree.
- Be in the first four years (full-time equivalent research experience) of their research careers.
- The Doctoral Candidate (DC) must not have resided or carried out their main activity (work, studies, etc.) in the country of the beneficiary (in this case: Spain) for more than 12 months in the 36 months immediately before their appointment.
- Strong mathematical background.
- Experience/knowledge on communications, 5G/6G, and/or Artificial Intelligence will be considered an asset.
- Track record of research excellence.
- Programming skills (Python, MATLAB, C++, etc).
- B2-C1 English Level.
- Good communications skills.
Languages ENGLISH
Benefits & conditions
The Doctoral Candidates (DC) enrolments are under very attractive employment conditions and competitive salaries offered in Marie Sklodowska Curie Doctoral Networks. The selected DCs will join a top-class research group and have a unique opportunity to pursue a career in wireless communications and networking. Working in this ambitious research project, DCs could lead to the successful completion of a doctoral degree, together with a very strong joint multidisciplinary research training program in the field of wireless and optical networks. The planned mobility is a plus of these job positions.
The Doctoral Candidates (DC) Fellowship is offered under very attractive employment conditions and competitive salaries in compliance with the MSCA Working Program. Salary is regulated by the EU total contributions that can reach 3833,56 € for the living allowance (country coefficient is applied), 710 € for the mobility allowance, and could be topped up with 495€ in case of family obligations. It should be highlighted that these amounts do not represent the gross salary but include all employer and employees' taxes and contributions. The period of employment is 3 years. The DC will take part in a secondment to NVIDIA for up to 6 months of their appointment period. The candidate will be enrolled in a PhD degree program. For work on site, the principal location will be the UOC Campus, at Rambla del Poblenou 154-156, Barcelona. At the UOC, we work with an open working model that combines remote working with work on-site, according to organizational needs and the nature of the tasks involved., * You'll be joining an organization with an open working model that combines teleworking with working on site.
- You'll be working in an environment where everyone has equal opportunities and equal access to resources and people, regardless of their location or teleworking choices.
- You'll be provided with the computer equipment and ergonomic material you need to work both from home and on site at the UOC.
- You'll have training possibilities to continue your professional development.
- You'll finish work early on Fridays.
- You'll have 24 days of vacation, 9 personal leave days and 4 UOC holidays.
- You'll be able to work reduced summer hours (35 hours a week), subject to organizational requirements.
- You'll have well-being benefits such as activities to look after your health, a medical service, a physiotherapy service and, if required, assessment and adaptation of your workplace.
Selection process
