Researcher Position in AI Native Networking for Healthcare
Division of Technology and Innovation, Section for Medical Information and Commu · Oslo, Norway
This two-year research role at Oslo University Hospital develops machine-learning methods for wireless network control and distributed learning in remote patient monitoring and hospital-at-home settings. The work focuses on network protocols, reinforcement learning, graph learning and federated learning, evaluated through simulation, emulation or testbeds.
Tech stack: Machine Learning, Wireless Networking, Reinforcement Learning, Multi-Agent Reinforcement Learning, Graph Neural Networks, Federated Learning, Network Simulation, Network Emulation, Edge Computing
About the role
The Section for Medical Information and Communication Technology (Medical ICT Research), The Intervention Centre, Oslo University Hospital, offers a full-time, two-year Researcher position in the Wireless Sensor Network Research Group of Professor Ilangko Balasingham.
We seek candidates with a solid background in computer networking who want to develop machine-learning methods for network control and network-aware distributed learning.
The research group has a strong scientific and technical background in wireless communications, machine learning and artificial intelligence, as well as radio frequency engineering and electronics. It collaborates closely with physician-scientists at the Intervention Centre. The Centre is internationally recognized for its scientific excellence and unique position in the field, promoting interdisciplinary research and development. You will work in a diverse and intellectually stimulating environment that fosters creativity, innovation, and scientific excellence in the development of future ICT-based healthcare solutions.
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!
Work Tasks
SYNAPSE, funded by the Research Council of Norway, develops networks that adapt their decisions to network conditions and the clinical urgency of the information they carry. Learning is integrated into network control to support decisions about scheduling, routing and resource allocation. For example, an urgent clinical alert should reach its destination promptly even when links are congested and patients are moving.
The project also develops distributed and federated learning methods that adapt to connectivity, available resources and clinical priorities. Network control and distributed learning are designed together, so that the network supports learning and learning remains effective when communication is constrained. The methods are evaluated in remote patient monitoring and hospital-at-home scenarios.
This position focuses on network protocols and their control at the MAC, network, transport and cross-layer levels, combined with machine learning. It does not cover hardware, antennas, circuits or physical-layer signal processing, and is not a general data-science position. Applicants must document relevant computer-networking knowledge and experience.
Research areas
- Learning-based network control, including scheduling, link selection, routing and resource allocation in wireless and edge networks.
- Reinforcement learning and multi-agent reinforcement learning for distributed network decision-making.
- Graph and hypergraph representation learning of network state, including temporal graph neural networks.
- Network- and urgency-aware distributed and federated learning, adapting the exchange of data and model updates to network conditions and clinical priorities.
- Evaluation through network simulation and emulation, and with real remote patient monitoring data.
Responsibilities
- Lead research on learning-based, urgency-aware network control and distributed learning that adapts to network state and clinical priority.
- Collaborate with the PhD fellow and master’s students.
- Publish in leading networking venues and contribute to project management and new proposals.
Kvalifikasjoner (overskrift)
Required Qualifications
- A PhD in computer networking, communications or computer science with a clear networking focus.
- Publications on networking topics and demonstrated experience developing or applying machine-learning methods to networking problems.
- Experience with network simulation, emulation or testbeds.
Preferred Qualifications
- Experience with multi-agent reinforcement learning, graph learning or federated learning.
- Experience supervising students or contributing to research proposals.
Language Requirements
- Very good written and spoken English.
Personal Qualities
- Ability to work independently and collaboratively.
- A structured, precise and adaptable working style.
- Strong communication and teamwork skills.
- A positive attitude and ability to manage a dynamic work environment.
- A high level of professionalism and work ethic.
We Offer
- A full-time, two-year Researcher position. Salary according to the applicable salary scale and qualifications. Researcher salary range to be confirmed by HR but will be within 600 000 - 650 000 kr per annum.
- Research collaboration with Dr Roufaida Laidi (PI), Prof. Ilangko Balasingham and Dr Hemin Ali Qadir, and with Prof. Tarik Taleb (Ruhr University Bochum).
- A clinical research environment at The Intervention Centre, Oslo University Hospital.
- Access to high-performance computing infrastructure at OUS and national e-infrastructure services.
- An inclusive, interdisciplinary research environment at the Intervention Centre, OUS.
- Pension, insurance and welfare schemes through the Norwegian public sector.
- Family-friendly surroundings with cultural and outdoor opportunities in Oslo.
Your application
Submit a cover letter of at most one page explaining your interest in SYNAPSE and your fit with the position. Identify:
Your computer-networking background, naming relevant coursework, a thesis, substantial projects or publications and explaining your own contribution.
Your experience implementing machine-learning methods and using network simulation, emulation or testbeds.
The research area or areas above that best match your background and interests.
Supporting documents
A CV with a list of publications
Transcripts for your bachelor’s, master’s and PhD degrees, with the grading scale or diploma supplement.
Copies of your diplomas.
Up to three relevant publications. Briefly explain their relevance to the position and your contribution in the cover letter.
Names and contact details of two referees, at least one academic. Referees must not be family members.
Documents not in English or a Scandinavian language must be accompanied by a certified translation. Applications without transcripts and diplomas will not be assessed.
Submit your application electronically through Webcruiter.
Kontaktinformasjon
Dr, Roufaida Laidi, Project leader, PI, [email protected]
Prof. Ilangko Balasingham, Section leader, [email protected]
Arbeidssted
Sognsvannsveien 20
0372 Oslo
Nøkkelinformasjon:
Arbeidsgiver: Oslo universitetssykehus HF
Referansenr.: 5200529751
Stillingsprosent: 100%
Engasjement
Startdato: 01.01.2027
Sluttdato: 31.12.2028
Søknadsfrist: 15.11.2026