Fully Funded PhD: AI-Native Networks for Healthcare

Dr. Ilangko Balasingham; Oslo; On-site; NOK 551,000 - 587,000; Full time

Benefits offered by this job

Fully funded 3-year PhD position

Pension and welfare schemes

Access to HPC infrastructure

Job summary

Oslo University Hospital invites applications for a fully funded 3-year PhD fellowship within the SYNAPSE project, focused on semantic hypergraph modeling and cross-layer MARL orchestration for healthcare networks.

The PhD candidate will join the SYNAPSE team at the Intervention Centre and collaborate with international partners, contributing to publications in top venues and advanced AI-driven networking research for remote patient monitoring.

Qualifications

• MSc degree in Computer Science, Electrical Engineering, or related field (120 ECTS) incl. 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)
• Solid background in ML/DL, GNNs, RL, Federated Learning or Network Optimization
• Proficiency in Python; experience with distributed systems is a plus

Responsibilities

• 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/ACM) and collaborative activities

Skills

ML/DL

GNN

Reinforcement Learning

Federated Learning

Education

MSc in CS/EE

BSc

Tools

PyTorch

TensorFlow

Job description

Oslo University Hospital invites applications for a fully funded 3-year PhD fellowship within the SYNAPSE project, focused on semantic hypergraph modeling and cross-layer MARL orchestration for healthcare networks.

The PhD candidate will join the SYNAPSE team at the Intervention Centre and collaborate with international partners, contributing to publications in top venues and advanced AI-driven networking research for remote patient monitoring.