This MSCA Doctoral Researcher position at Tampere University offers a unique opportunity to contribute to the future of smart, sustainable mobile machinery through long-term 3D mapping of dynamic construction sites. The project is part of the ENGAGE network, which brings together leading machine manufacturers, technology companies, and academic groups across Europe to train engineers in cutting-edge fields such as AI, robotics, and mechanical engineering. The research will focus on developing methods and tools for creating and maintaining semantic 3D maps of worksites, modelling 3D environments, and integrating new environmental measurements to capture dynamic changes. The doctoral candidate will explore approaches for semantic labelling of environments, intelligent partitioning of models, and efficient updating of 3D maps as people, objects, and materials move within the space. Training will cover state-of-the-art topics including ML-based 3D reconstruction, semi-supervised semantic labelling, sensor fusion, and dynamic environment modelling. The position is full-time for three years, with employment split between Tampere University in Finland (12 months) and Volvo CE in Sweden (24 months). The target degree is a doctoral degree from Tampere University. The supervisory team includes Professors Esa Rahtu and Reza Ghabcheloo from Tampere University, and Mohammad Loni from Volvo CE. The gross salary is approximately 3800 EUR/month in both Finland and Sweden, with family allowance available if applicable, and is defined according to MSCA funding rules. Applicants must hold an MSc in a relevant engineering discipline or applied mathematics, be eligible for doctoral studies at Tampere University, and comply with the MSCA Mobility Rule. Proficiency in English is required, and experience in computer vision, dynamic 3D modelling, semantic labelling, and deep learning is appreciated. The application process requires submission of degree certificates, CV, motivation letter, and proof of residence through the LAURA portal by November 16, 2025. Early applications are encouraged as interviews may begin during the application period. The position offers a dynamic research environment, collaboration with industry leaders, and the chance to work in two countries, contributing to the advancement of autonomous and digital solutions for mobile working machines.

This MSCA Doctoral Researcher position at Tampere University focuses on safe navigation for mobile working machines (MWM) on rough and dynamic terrain, such as construction sites. The project is part of the ENGAGE network, which brings together leading machine manufacturers, technology companies, and academic groups across Europe to advance green, autonomous, and digital solutions for mobile machinery. The doctoral researcher will develop methods for building traversability costs from real-time sensor data and integrate these costs into safety controllers, contributing to both industry and scientific objectives. Training will cover state-of-the-art topics including model predictive control, control barrier certificates, real-time 3D sensing and mapping, and machine learning-based sensing and control. The candidate will also participate in dissemination activities through social media and digital platforms. The position is full-time for three years, with employment split between Tampere University (12 months) and Volvo CE in Sweden (24 months). The target degree is a doctoral degree from Tampere University. The gross salary is approximately 3800 EUR/month in both countries, with family allowance available if applicable, and is defined according to MSCA funding rules. Applicants must hold an MSc in a relevant engineering discipline or applied mathematics, be eligible for doctoral enrollment, and comply with the MSCA Mobility Rule. Proficiency in English is required, and experience with computer vision, dynamic 3D modelling, semantic labelling, and deep learning is valued. The application deadline is November 16, 2025, and early applications are encouraged as interviews may begin during the application period. The supervisory team includes Professor Reza Ghabcheloo, Dr. Gokhan Alcan, and Dr. Mohammad Loni. The position offers a unique opportunity to work in a multidisciplinary, high-impact research environment and to contribute to the future of smart, sustainable mobile machinery.