PhD Fellowship in AI-native Networks

Arbeidsplassen; Oslo; On-site; NOK 551,000 - 587,000; Full time

Benefits offered by this job

Fully funded PhD position

Norwegian state salary scale

HPC infrastructure access

Job summary

Oslo University Hospital offers a fully funded 3-year PhD Fellowship in the SYNAPSE project. The recruited PhD Fellow will join the Wireless Sensor Network Research Group and is enrolled in the PhD program at the University of Oslo.

Supervision by senior researchers and international collaboration are core elements. The project focuses on semantic hypergraph modeling, dynamic link control, and MARL orchestration to improve latency, reliability, and energy efficiency in healthcare networks.

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, Graph Neural Networks, Reinforcement Learning, Federated Learning, or Network Optimization, with solid Python programming

Responsibilities

• Conduct research in AI-native networking for healthcare applications
• Design and implement graph neural network models and multi-agent reinforcement learning frameworks
• Validate outcomes under realistic network conditions including mobility, congestion, and heterogeneous workloads
• Contribute to scientific publications in top-tier venues (NeurIPS, IEEE Trans. Networking, ACM Internet Tech) and collaborative activities

Skills

Machine Learning / DL

Graph Neural Networks

Reinforcement Learning

Federated Learning

Python

Education

MSc in CS or EE (120 ECTS)

BSc (180 ECTS)

Tools

PyTorch

TensorFlow

Job description

TIK, Section for medical information and communication technology, Oslo University Hospital HF

About the research group Section for Medical Information and Communication Technology (Medical ICT Research), The Intervention Centre (see: http://www.ivs.no), at Oslo University Hospital offers a full-time PhD Fellowship. The recruited PhD Fellow will be part of theWireless Sensor Network Research Groupof Professor Ilangko Balasingham and will be enrolled in the PhD program at the University of Oslo Oslo University Hospital is a workplace with great diversity. We believe this is crucial for solving our tasks in the best possible way. We want this diversity to be reflected among the applicants for our positions, and we encourage all qualified candidates, regardless of background, to apply!

The fellowship is part of the SYNAPSE (SYnergetic Network-AI Platform for Semantic Efficiency) project, funded by the Research Council of Norway (12 MNOK).

SYNAPSE addresses a critical gap in next-generation networks: the disconnect between distributed AI processes and network infrastructure. The project develops an AI-native ecosystem where communication and computation co-evolve through cross-layer awareness, integrating semantic hypergraph intelligence, urgency-weighted federated learning, and multi-agent reinforcement learning for mission-critical healthcare applications. The framework is validated through remote patient monitoring scenarios, targeting substantial improvements in latency, reliability, and energy efficiency.

For more information, visit the SYNAPSE project page at: https://www.linkedin.com/company/synapse-ous Supervision by Dr. Roufaida Laidi (PI), Prof. Ilangko Balasingham, and Dr. Hemin Qadir International collaboration network, including partners at Ruhr University Bochum, Germany.

About the research group Section for Medical Information and Communication Technology (Medical ICT Research), The Intervention Centre (see: http://www.ivs.no), at Oslo University Hospital offers a full-time PhD Fellowship. The recruited PhD Fellow will be part of theWireless Sensor Network Research Groupof Professor Ilangko Balasingham and will be enrolled in the PhD program at the University of Oslo Oslo University Hospital is a workplace with great diversity. We believe this is crucial for solving our tasks in the best possible way. We want this diversity to be reflected among the applicants for our positions, and we encourage all qualified candidates, regardless of background, to apply!

The fellowship is part of the SYNAPSE (SYnergetic Network-AI Platform for Semantic Efficiency) project, funded by the Research Council of Norway (12 MNOK).

SYNAPSE addresses a critical gap in next-generation networks: the disconnect between distributed AI processes and network infrastructure. The project develops an AI-native ecosystem where communication and computation co-evolve through cross-layer awareness, integrating semantic hypergraph intelligence, urgency-weighted federated learning, and multi-agent reinforcement learning for mission-critical healthcare applications. The framework is validated through remote patient monitoring scenarios, targeting substantial improvements in latency, reliability, and energy efficiency.

For more information, visit the SYNAPSE project page at: https://www.linkedin.com/company/synapse-ous 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 Project leader/PI: Dr. Roufaida Laidi – [e-mail] Prof. Ilangko Balasingham – i.s.balasingham@ous-research

Oslo University Hospital is a workplace with great diversity. We believe this is crucial for solving our tasks in the best possible way. We want this diversity to be reflected among the applicants for our positions, and we encourage all qualified candidates, regardless of background, to apply!

Arbeidsoppgaver

• 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

  ability to solve complex challenges, and we encourage all qualified candidates to apply regardless of background.

• Responsibilities

  The PhD candidate will:

  • Conduct research in AI-native networking and semantic hypergraph intelligence for healthcare applications
  • 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

Kvalifikasjoner (overskrift)

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
• Interest in healthcare AI applications and interdisciplinary collaboration
• Experience with HPC environments and large-scale experiments

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 hospital
• Salary according to the Norwegian state salary scale (approx. NOK 550,800–587,000/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

Kontaktinformasjon

Dr. Roufaida Laidi, Project leader/PI, [e-mail]

Dr. Ilangko Balasingham, Head of Section, Professor, [e-mail]

Arbeidssted

Sognsvannsveien 20

0372 Oslo

Nøkkelinformasjon:

Arbeidsgiver: Oslo universitetssykehus HF

Referansenr.: 5169482980

Stillingsprosent: 100%

Engasjement

Søknadsfrist: 13.09.2026

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 University Hospital is responsible for approximately 50 percent of all medical and healthcare research conducted at Norwegian hospitals and is a significant role player within the education of a large variety of health care personnel. We are an emergency hospital for East and Southern Norway and have national emergency assignments. The hospital has a total budget of NOK 17 billion. More than 20,000 employees are engaged with activities at more than 40 different locations.

The University of Oslo is Norway's oldest and highest rated institution of research and education with 28 000 students and 7000 employees. Its broad range of academic disciplines and internationally esteemed research communities make UiO an important contributor to society. The Faculty of Medicine was established in 1814 and is the oldest medical faculty in Norway. The Faculty is organized into three basic units and has approximately 1,500 employees and about 2000 students.