Thesis: Multimodal Spatiotemporal Intelligence for Fleet-Level Intelligence Op Decision Support

Volvo Group; Göteborgs kommun; On-site; SEK 134,000 - 201,000; Part time

Job summary

Volvo Group’s Volvo Autonomous Solutions is seeking a master’s thesis student to investigate how shared information from multiple vehicles can be used to detect changing site conditions and support operational decision-making across a fleet.

You will work with multi-modal vehicle data, CAN signals, maps and events, applying Python-based deep learning tools (PyTorch or TensorFlow) under expert supervision.

Qualifications

• Enrolled in a master’s programme in computer science, data science, machine learning, electrical engineering, robotics or related field.
• Strong Python programming skills and hands-on experience with PyTorch or TensorFlow.
• Interested in autonomous systems, machine perception, spatiotemporal modelling and real-world sensor data.
• Independent, structured and curious; analytical and motivated to solve technical problems.
• Proficient in written and spoken English.

Responsibilities

• Develop and compare approaches for modelling changing site conditions over time.
• Combine information from vehicle sensors, CAN signals, maps and events.
• Demonstrate evidence-grounded recommendations for fleet-level decision support.
• Measure detection quality, lead time, false alarms and robustness to missing sensors.
• Evaluate generalisation across vehicles and operating conditions.
• Document results in a scientific report.

Skills

Python

PyTorch

TensorFlow

English

Education

Master's program in CS/DS/ML/EE/Robotics

Tools

CUDA

Job description

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Location:

Göteborg, SE, 417 15

Position Type: Student

Permanent/Temporary: Temporary

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.

At Volvo Autonomous Solutions, we are at the forefront of innovation, designing the autonomous transport solutions of tomorrow. As part of our global and diverse team, you will have the opportunity to work on an industrial research challenge that contributes to the future of safe, efficient and sustainable transport.

We are looking for a master’s thesis student to investigate how shared information from multiple vehicles can be used to detect changing site conditions and support operational decision-making across a fleet.

The thesis project

Conditions observed by one vehicle may affect vehicles that subsequently approach the same area. For example, changes in road conditions, traffic situations or operational environments may have an impact on vehicle safety, routing and mission execution.

The goal of this thesis is to investigate whether a shared spatiotemporal representation of sensor observations, vehicle signals, maps and operational events can be used to maintain a dynamic model of site conditions. The representation should also be reusable for applications such as ODD monitoring, road-condition assessment, mission assistance, traffic coordination, incident investigation and maintenance analysis.

The project will include developing and comparing timestamp-based, single-modality and multimodal methods for maintaining a dynamic site-condition model. You will also investigate how the model can provide evidence-grounded recommendations, such as warning another vehicle, identifying an affected route or proposing a review of speed, routing or traffic-control settings.

The work will include:

• Developing and comparing different approaches for modelling changing site conditions over time.
• Combining information from vehicle sensors, CAN signals, maps and operational events.
• Demonstrating evidence-grounded recommendations for fleet-level decision support.
• Measuring detection quality, warning lead time, false alarms and robustness to missing sensors.
• Evaluating how well the approach generalises across vehicles and operating conditions.
• Analysing the results and documenting your findings in a scientific report.

Resources and research environment

You will have access to multi-vehicle camera, CAN and operational data, as well as position data, site maps and reviewed events or condition changes. GPU compute resources and multimodal models will be available for developing and evaluating your approach.

Additional sensor data from LiDAR and RADAR may also be available, depending on the selected scope of the project. You will work closely with experienced engineers and researchers in a collaborative AI and autonomy team, gaining insight into fleet-level intelligence, autonomous systems and the development of operational decision-support solutions.

Who are you?

You are enrolled in a master’s programme in computer science, data science, machine learning, electrical engineering, robotics or a related field. You have solid Python programming skills and hands-on experience with a deep-learning framework such as PyTorch or TensorFlow.

We are looking for someone who is interested in autonomous systems, machine perception, spatiotemporal modelling and working with real-world sensor and vehicle data.

You should also be:

• Independent, structured and curious.
• Analytical and motivated to solve challenging technical problems.
• Comfortable working with multimodal data, machine-learning experiments and evaluation metrics.
• Interested in fleet-level intelligence and operational decision support.
• Proficient in written and spoken English.

What’s in it for you?

This thesis gives you the opportunity to work on a real industrial research problem with access to unique multimodal vehicle data and the tools needed to conduct advanced experiments. You will receive close technical supervision from experts in AI and autonomous systems, as well as access to GPU resources and multimodal models. You will also become part of a dynamic and inclusive work environment where new ideas are encouraged and celebrated.

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.

Part of Volvo Group, Volvo Autonomous Solutions accelerates the development, commercialization and sales of autonomous transport solutions, focusing on defined segments for the on- and off-road space. The combination of strong tech expertise and skilled customer solutions creates innovative transport offers never seen before. We are constantly pushing our own skills and ability to drive change in a traditional industry to meet a growing customer demand. We are now looking for innovative, committed individuals to join us in our endeavor to create customer solutions that enhance safety, flexibility and productivity.

Job Category: Technology Engineering

Organization: Volvo Autonomous Solutions

Every day, Volvo Group products and services ensure that people have food on the table, children arrive safely at school and roads and buildings can be constructed. Looking ahead,we are committed to driving the transition to sustainable and safe transport, mobility and infrastructure solutions toward a net-zero society.

Joining Volvo Group, you will work with some of the world’s most iconic brands and be part of a global and leading industrial company that is harnessing automated driving, electromobility and connectivity.

Our people are passionate about what they do, they aim for high performance and thrive on teamwork and learning. Everyday life at Volvo is defined by a climate of support, care and mutual respect.

If you aspire to grow and make an impact, join us on our journey to create a better and more resilient society for the coming generations.