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.