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

Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning

In short

This master's thesis project at Volvo Autonomous Solutions in Gothenburg, Sweden, focuses on using multimodal spatiotemporal intelligence to support fleet-level operational decisions. You will investigate how shared vehicle information can detect changing site conditions and develop methods for maintaining a dynamic model of these conditions, providing evidence-grounded recommendations for enhanced safety and efficiency in autonomous transport.

Responsibilities

Investigate how shared information from multiple vehicles can detect changing site conditions and support operational decision-making across a fleet.
Develop and compare timestamp-based, single-modality, and multimodal methods for maintaining a dynamic site-condition model.
Investigate how the model can provide evidence-grounded recommendations (e.g., warnings, route adjustments, speed settings).
Measure detection quality, warning lead time, false alarms, and robustness to missing sensors.
Evaluate how well the approach generalises across vehicles and operating conditions.
Analyse results and document findings in a scientific report.

Requirements

Enrolled in a master’s programme in computer science, data science, machine learning, electrical engineering, robotics, or a related field.
Solid Python programming skills.
Hands-on experience with a deep-learning framework such as PyTorch or TensorFlow.
Interest in autonomous systems, machine perception, spatiotemporal modelling, and working with real-world sensor and vehicle data.
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.

Benefits

Opportunity to work on a real industrial research problem.
Access to unique multimodal vehicle data and tools for advanced experiments.
Close technical supervision from experts in AI and autonomous systems.
Access to GPU resources and multimodal models.
Part of a dynamic and inclusive work environment where new ideas are encouraged and celebrated.

Skills

PythonPyTorchTensorFlow

#autonomous systems#machine perception#spatiotemporal modelling#sensor data#vehicle data#fleet-level intelligence#decision support#AI#computer science#data science#machine learning#electrical engineering#robotics

About Volvo Group

The Volvo Group is one of the world’s leading manufacturers of trucks, buses, construction equipment and marine and industrial engines. The Group also provides complete solutions for financing and service. The Volvo Group, with its headquarters in Gothenburg, employs about 100,000 people, has production facilities in 18 countries and sells its products in more than 190 markets.\n\n

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