Master thesis: Pipeline to Simulate Federated Learning in Edge Devices Lundby 2025

Job description

Transport is at the core of modern society. Imagine using your expertise to shape sustainable transport and infrastructure solutions for the future? If you seek to make a difference on a global scale, working with next-gen technologies and the sharpest collaborative teams, then we could be a perfect match. 

Who are we

The Volvo Group is one of the world’s leading manufacturers of trucks, buses, construction equipment, and marine and industrial engines under the leading brands Volvo, Renault Trucks, Mack, UD Trucks, Eicher, SDLG, Terex Trucks, Prevost, Nova Bus, UD Bus, Dongfeng, Sunwin Bus and Volvo Penta.

Volvo Group Trucks Technology encompasses the production of state-of-the-art products for the truck brands of the Volvo Group, as well as Volvo Group engines and transmissions, through an international world class industrial environment.

With Volvo Group Trucks Technology, you will be part of a global and diverse team of highly skilled professionals working with energy, passion and respect for the individual to become the world leader in sustainable transport solutions.

Background of thesis project

Federated learning has gained a lot of traction in recent times, with a core focus on data security and privacy. Model management and the associated pipeline are the key success factors in a federated learning environment.

Along with model management, fault tolerance and recovery mechanisms play a crucial role in the overall pipeline.

This thesis project focuses on simulating a federated learning environment using Raspberry Pis (or similar) as edge devices. The research focuses on the pipeline’s ability to handle device failures, unstable network connections and interruptions. The solution also needs to implement model checkpoint- and edge caching strategies, or rollback functionality to prevent disruption in training.

Description of thesis work

The aim of this project is to simulate a federated learning environment using Raspberry Pis (or similar) as edge devices. The research focuses on the pipeline’s ability to handle device failures, unstable network connections and interruptions.

 

Methodology

·  Study of relevant theories and principles, and existing research papers, related to edge computing and federated learning.
·  Simulate a federated learning environment using Raspberry Pis (or similar) as edge devices.

Suitable background

Field of Study:

·  Distributed Computing & Systems

Thesis Level: Master

Language: Thesis is to be written in English.

Starting date: February 1st, 2025

Number of students: 2

Contact: Emelie Havseld - Manager Build, Test & Data Solutions - emelie.havseld@volvo.com

We value your data privacy and therefore do not accept applications via mail. 

 

Who we are and what we believe in 
Our focus on Inclusion, Diversity, and Equity allows each of us the opportunity to bring our full authentic self to work and thrive by providing a safe and supportive environment, free of harassment and discrimination. We are committed to removing the barriers to entry, which is why we ask that even if you feel you may not meet every qualification on the job description, please apply and let us decide.

 

Applying to this job offers you the opportunity to join Volvo Group . Every day, across the globe, our trucks, buses, engines, construction equipment, financial services, and solutions make modern life possible. We are almost 100,000 people empowered to shape the future landscape of efficient, safe and sustainable transport solutions. Fulfilling our mission creates countless career opportunities for talents with sharp minds and passion across the group’s leading brands and entities. 

 

Group Trucks Technology are seeking talents to help design sustainable transportation solutions for the future. As part of our team, you’ll help us by engineering exciting next-gen technologies and contribute to projects that determine new, sustainable solutions. Bring your love of developing systems, working collaboratively, and your advanced skills to a place where you can make an impact. Join our design shift that leaves society in good shape for the next generation.

Job Category:  Advanced Analytics

Organization:  Group Trucks Technology

Travel Required:  No Travel Required

Requisition ID:  15387