Master Thesis - Deep Learning-Based Virtual CO₂ Sensor for Truck Cabin Environment

Introduction
Transport is at the core of modern society. Imagine using your expertise to shape sustainable transport 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. 

This is an opportunity for you to apply your academic learnings in Machine Learning on an advanced, hands-on industrial application by performing your master thesis project at Volvo Group Trucks Technology. 

Who we are
Thermal Management is a department within Volvo Group Trucks Technology with the responsibility for developing optimized Vehicle Thermal Management Systems for all truck brands within the Volvo Group.

As a master thesis student in the Data Analytics and Machine Learning team within the Thermal Management department you will be a valued contributor to our continuous learning. You will be surrounded by a global and diverse team of highly skilled and engaged colleagues who will be interested in the progress of your work and eager to help and support you along the way.

Thesis objectives
•    Develop a data-driven virtual sensing model for CO₂ concentration estimation using Deep Learning / AI techniques.
•    Collect, preprocess, and analyze multi-sensor vehicle and HVAC data.
•    Evaluate different model architectures (e.g., LSTM, GRU, CNN, Transformer, or hybrid models) for virtual sensing accuracy and robustness.
•    Benchmark virtual sensor performance against physical CO₂ sensor measurements.
•    Demonstrate integration feasibility of the virtual sensor into the cabin climate control system.

Key responsibilities
•    Conduct literature review on virtual sensing, air quality estimation, and sensor fusion techniques.
•    Work closely with data scientists and control engineers to understand system behavior and data dependencies.
•    Perform data preprocessing, feature engineering, and model training using Python-based ML frameworks.
•    Validate and document the developed model’s performance on test datasets and vehicle-level data.
•    Present findings and propose future enhancements for production deployment.

Required qualifications
•    Strong background in Machine Learning / Deep Learning (TensorFlow, PyTorch, or similar).
•    Good understanding of time-series data analysis and sensor data modeling.
•    Programming experience in Python (NumPy, Pandas, Scikit-learn, etc.).
•    Basic knowledge of automotive systems, HVAC control, or virtual sensing is a plus.
•    Analytical mindset and excellent problem-solving skills 
•    Fluent in English

What we offer
•    Opportunity to work on a real-world industry problem with a clear path to production deployment.
•    Hands-on exposure to automotive data, virtual sensing, and climate control system optimization.
•    Guidance and mentorship from experienced AI engineers and domain experts.
•    Access to cutting-edge tools and datasets used in vehicle system development.
•    A chance to contribute to future-ready sustainable vehicle technologies.

Thesis level: Master, 30 ECTS credits
Number of students: 1-2
Start date: January 2026, or upon agreement
Industrial supervisor: Krishna Hariharan, krishna.hariharan.m@volvo.com 
Location: Volvo Lundby site, Gothenburg, Sweden
Last application date: December 7, 2025


We look forward to receiving your application!

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

Who we are and what we believe in 
We are committed to shaping the future landscape of efficient, safe, and sustainable transport solutions. Fulfilling our mission creates countless career opportunities for talents across the group’s leading brands and entities.

Applying to this job offers you the opportunity to join Volvo Group. Every day, you will be working with some of the sharpest and most creative brains in our field to be able to leave our society in better shape for the next generation. ​We are passionate about what we do, and we thrive on teamwork. ​We are almost 100,000 people united around the world by a culture of care, inclusiveness, and empowerment. 

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.