Master's thesis; Next-Generation Connectivity and Edge AI for Industry Use Cases
We are looking for 4–5 motivated Master’s thesis students to join the Digital Testbed Sweden (DTSE) initiative. Together, you will explore how next-generation technologies like 5G, Edge AI, and IoT can be applied to real-world challenges in smart recycling (Boden) and smart & safe ports (Luleå).
About the project
Digital Testbed Sweden is a collaborative innovation platform demonstrating how digital infrastructure can drive sustainability, safety, and efficiency across industries.
- Shared technical backbone: All students will contribute to a common pipeline for sensing, connectivity, edge inference, operator interfaces, and cloud-based learning.
- Diverse applications: Each student will focus on a specific use case, such as:
- Port safety & inspection (Luleå) – drone inspections, hazard detection, smart surveillance.
- Smart recycling (Boden) – AI-based detection and removal of plastics from recycled materials.
- Comparative studies: A key objective will be to perform comparative analysis across technologies, for example:
- 4G vs 5G – understanding the impact of network characteristics (latency, jitter, throughput) on different use cases.
- Edge vs Cloud inference – evaluating how deployment location affects latency, performance, cost, and reliability, especially for safety-critical or real-time scenarios.
Key Responsibilities
As a thesis student, you will:
- Design, implement, and test components of the end-to-end pipeline (sensors, gateways, AI inference, operator dashboards, cloud retraining).
- Apply your work to one of the real-world pilot cases (port safety or recycling).
- Conduct comparative experiments (networks and edge vs. cloud inference) to evaluate trade-offs for industrial use cases.
- Collaborate closely with other students to ensure interoperability and shared learnings.
- Final report (Master thesis)
- Document your findings and contribute to best practices for deploying 5G + Edge AI solutions.
Qualifications
- Master’s student in Computer Science, Electrical Engineering, AI/ML, Data Science, or related fields.
- Skills in one or more of the following areas:
- AI/ML frameworks (PyTorch, TensorFlow, ONNX, OpenVINO)
- Computer vision / sensor data processing
- IoT protocols (MQTT, LoRa, NB-IoT) and gateways
- Networking concepts (latency, QoS, MEC)
- Edge/cloud platforms (Kubernetes, Docker)
- Strong interest in applied research and industry collaboration.
Terms
- Scope: 30 hp, full-time
- Location: Luleå
- Start: Flexible
- Compensation: For an approved master’s thesis comprising 30 credits, we pay a compensation of SEK 39,990 if there is one student, or SEK 30,000 per student if there are multiple students.
Welcome with your application!
For more details contact – Richa Upadhyay (richa.upadhyay@ri.se)
Supervisors
- Martin Simonsson (martin.simonsson@ri.se)
- Richa Upadhyay (richa.upadhyay@ri.se)
The application deadline is November 14, 2025.
Please note: You need to have the right to reside in Sweden during the thesis period without requiring us as a company to arrange a visa or work permit.