Phd Fellowship in Ai-native Networking

PhD Fellowship in AI-Native Networking
- TIK, Section for Medical Information and Communication Technology, Oslo University Hosital HF
- (i ny fane)
- Om stillingen
Nøkkelinformasjon
- Søknadsfrist:
** **
- Arbeidsgiver:
**Oslo universitetssykehus HF**
- Sted:
**Oslo**
- Stillingstittel:
**PhD Fellowship in AI-Native Networking**
- Stillinger:
**1**
- Heltid / Deltid:
**Heltid**
- Ansettelsesform:
**Fast**
- Stillingsprosent:
**100**
- Webcruiter-ID:
** **
- Del på X- Del på LinkedIn- Del på Facebook- Del på e-postThe fellowship is part of the SYNAPSE (SYnergetic Network-AI Platform for Semantic Efficiency) project, funded by the Research Council of Norway (12 MNOK).
Supervision by Dr. Roufaida Laidi (PI), Prof. Ilangko Balasingham, and Dr. Hemin Qadir
International collaboration network, including partners at Ruhr University Bochum, Germany
**Contact Information**
**About the PhD Project**
The PhD fellow will be a core member of the SYNAPSE team and will focus primarily on Work Package 1 (Semantic Hypergraph Modeling and Dynamic Link Control), with contributions to Work Package 3 (Cross-Layer MARL Orchestration). The research will include:
- Designing and formalizing semantic hypergraph representations that encode urgency propagation paths, device relationships, and resource constraints in distributed networks
- Developing and training temporal Graph Neural Networks (GNNs) to produce unified embeddings capturing both network dynamics and semantic priorities
- Integrating hypergraph embeddings into multi-agent reinforcement learning frameworks to enable coordinated, real-time link control decisions
- Implementing decentralized link adaptation mechanisms for predictive rerouting and prioritization of critical data flows
Validating the framework under realistic conditions including mobility, congestion, and heterogeneous workloads
**Responsibilities**
- Design and implement graph neural network models and multi-agent reinforcement learning frameworks for cross-layer network orchestration
- Validate research outcomes under realistic network conditions including mobility, congestion, and heterogeneous workloads Contribute to scientific publications in top-tier venues (e.g., NeurIPS, IEEE Transactions on Networking, ACM Internet Technology) and collaborative research activitie
**Required Qualifications**:
- MSc degree in Computer Science, Electrical Engineering, or a related field (120 ECTS), including a thesis
- BSc degree (180 ECTS)
- Strong academic performance (minimum grade B; A preferred)
- Master’s thesis graded B or better (Norwegian system or equivalent)
- Strong background in:
- Machine Learning / Deep Learning (PyTorch or TensorFlow)
- Graph Neural Networks, Reinforcement Learning, Federated Learning, or Network Optimization (at least one)
- Solid Python programming; experience with distributed or networked systems is a plus Publication record is an advantage
**Preferred Qualifications**:
- Experience with semantic communication, network simulation, or software-defined networking
- Familiarity with hypergraph or higher-order network models
- Publications in relevant peer-reviewed venues
**Language Requirements**:
- Applicants who are not proficient in a Scandinavian language must document English proficiency through one of the following: TOEFL: 600 (paper-based) or
- 92 (internet-based) IELTS (Academic):
- 6.5 (no section below 5.5)
- Cambridge CAE/CPE: Grade A or B
**Personal Qualities**:
- Ability to work independently and collaboratively
- Structured, precise, and adaptable working style
- Strong communication and teamwork skills
- Positive attitude and ability to manage a dynamic work environment
- High level of professionalism and work ethic
**We Offer**
- A fully funded 3-year PhD position at one of Europe’s leading university hospitals
- Salary according to the Norwegian state salary scale (approx. NOK 536,200-587,000/year)
- Access to high-performance computing infrastructure at OUS and national e-infrastructure services
- An inclusive, interdisciplinary research environment at the Intervention Centre, OUS
- Generous benefits including pension, insurance, and welfare schemes through the Norwegian public sector Family-friendly surroundings with excellent cultural and outdoor opportunities in Oslo
- Adresse:
- Sognsvannsveien 20, 0372 Oslo, Norge
**(i ny fane)**
Kontaktinformasjon
**Roufaida Laidi**
- Project leader
- E-post:
**Ilangko Balasingham**
- Section leader/professor
- E-post:
Om arbeidsgiveren
Oslo University Hospital is a highly specialised hospital in charge of extensive regional and local hospital assignments and the provision of high quality services for the citizens of Oslo. The hospital also has a nationwide responsibility for a number of national and multi-regional assignments and has several national centres of competence. The hospital is Scandinavia's largest and we each year carry out more than 1.2 million patient treatments. Oslo Unive