Master Thesis: Design and Optimization of a Dynamic Reduced-Order Model for Performance - Radio Unit
About this opportunity
Ericsson is offering a Master thesis opportunity within Thermal System Performance in Lund, Sweden. The work focuses on developing and validating a computationally efficient thermal digital twin for fast prediction of transient temperature behaviour in telecom radio units under realistic traffic scenarios.
As mobile communication traffic becomes increasingly dynamic and energy-saving features are introduced, understanding temperature evolution over time is becoming more important. High-fidelity commercial electronics-cooling simulations can describe this behaviour, but they often require significant computational effort and are not always practical for repeated or near real-time analysis.
In this thesis, you will develop a dynamic reduced-order thermal model that can be implemented in MATLAB, Simulink, Python, or an equivalent environment for rapid analysis of the time-dependent thermal behaviour of a telecom radio unit.
You will use available simulation models and commercial simulation software to generate input and reference data, then calibrate and validate the reduced-order model against high-fidelity simulation results.
The work includes investigating the trade-off between model fidelity and computational performance, with the aim of enabling fast or near real-time thermal prediction of complex telecom radio units.
Possible modelling approaches include RC-network representations, state-space formulations, system-identification methods, Proper Orthogonal Decomposition, or hybrid physics-informed data-driven methods. You will select and justify the final approach based on accuracy, interpretability, implementation complexity, and suitability for dynamic thermal prediction.
You will also assess how modelling assumptions, model structure, parameter selection, and numerical stability influence the ability to reproduce transient thermal behaviour, including the balance between computational speed, prediction accuracy, and physical relevance.
What you will do
- Perform a literature study covering transient thermal modelling, reduced-order modelling, and relevant digital-twin approaches.
- Develop, implement, calibrate, and validate a dynamic reduced-order thermal model.
- Compare the model with high-fidelity simulation data using relevant accuracy, stability, and performance metrics.
- Analyse sensitivity, robustness, assumptions, limitations, and validity range under different operating conditions.
- Document the results and provide recommendations for how the model can be further developed or applied.
The skills you bring
You are a Master's student in Mechanical Engineering, Engineering Physics, Applied Physics, or a related field.
Knowledge of heat transfer, fluid mechanics, numerical methods, system modelling, or control theory is beneficial.
Experience with MATLAB, Simulink, Python, or equivalent tools is an advantage, together with a strong interest in thermal modelling, simulation, and applied product development.
Skills Required
- Currently pursuing a Master's degree in Mechanical Engineering, Engineering Physics, Applied Physics, or a related field
- Knowledge of heat transfer, fluid mechanics, numerical methods, system modelling, or control theory
- Experience with MATLAB, Simulink, Python, or equivalent tools
- Strong interest in thermal modelling, simulation, and applied product development
What the Team is Saying
.png)
.png)
What We Do
Ericsson builds the digital connectivity the world relies on. Our technology underpins the mobile networks, platforms, and systems that billions of people, businesses, and societies depend on every day. We are a global leader in communications technology, delivering mobile network infrastructure, cloud software, and wireless connectivity solutions for service providers and enterprises worldwide. Our networks support connectivity across 180+ countries, helping power everyday communication as well as critical digital services at global scale. Connectivity has evolved far beyond consumer mobile use. Today, nearly 80% of the world’s population accesses the internet via mobile networks, and Ericsson is helping shape what comes next. We are advancing 5G and 5G Advanced, developing network APIs that open connectivity to the global developer ecosystem, and applying automation and AI to make networks more intelligent, efficient, and resilient. Ericsson was the first company to launch live 5G networks on five continents, and our 5G platform is now commercially live in 150+ networks across 60+ countries. We also support more than 36,000 enterprise customers, enabling secure, high-performance connectivity for industries such as manufacturing, aviation, logistics, utilities, and public safety, where reliability and performance are mission critical. Innovation is central to how we work. Ericsson has approximately 28,000 employees in research and development, backed by one of the strongest intellectual property portfolios in the industry with 60,000+ granted patents. Our engineers, researchers, and technologists work across 100+ global R&D sites, helping define how networks evolve and how digital infrastructure is built for the long term. As the world moves toward a mobile-first, AI-powered, and cloud-driven future, connectivity becomes the foundation for digital transformation across every industry. Ericsson is building that foundation, shaping the future of digital connectivity through technology that operates at global scale and supports real-world impact, today and for what comes next.
Why Work With Us
Ericsson is a place for people who want to work on technology that powers everyday life. You’ll contribute to large-scale systems used every day, tackle complex challenges in live environments, and keep developing your skills and career in your own vision.
Gallery
.jpg)
.jpg)
.jpg)
.jpg)
.jpg)
Ericsson Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Ericsson adopts a hybrid work model globally because we know balance matters. Sometimes things are better in real life. Other times we can be more productive at home. Our hybrid approach gives you the best of both worlds.
