This MSCA Doctoral Researcher position at Tampere University focuses on developing predictive models for contact-rich construction tasks, specifically targeting force and energy loss prediction in hydraulic machines. The project is part of the ENGAGE network, which brings together leading machine manufacturers, technology companies, and academic groups across Europe to advance smart, sustainable mobile machinery. The doctoral researcher will work on both industry and scientific objectives, including the creation of data-efficient models for hydraulic machines operating with heterogeneous materials and the development of advanced control algorithms to enhance operational efficiency and safety. Scientific goals include leveraging simulations and domain knowledge to build innovative machine learning models that accurately predict forces and energy losses, as well as designing predictive control strategies to manage complex machine behaviors in real time. Training will cover state-of-the-art topics such as simulation, reinforcement learning, imitation learning, and model predictive control. The position offers a multidisciplinary environment, with employment split between Tampere University and Novatron, a company specializing in machine control systems and cloud services for construction sites. The doctoral candidate will also participate in dissemination activities, including social media, blogging, and video content. Applicants must hold an MSc in a relevant engineering discipline or applied mathematics, meet the MSCA Mobility Rule, and demonstrate proficiency in English. The position is fully funded for three years, with a gross salary of approximately 3800 EUR/month and potential family allowance. The application process requires submission of degree certificates, CV, motivation letter, and proof of residence via the university's online portal. The application deadline is November 16, 2025, and early applications are encouraged as interviews may begin during the application period. Supervisors include Assistant Professor Gokhan Alcan and Professor Reza Ghabcheloo from Tampere University, and Antti Kolu from Novatron. The research will contribute to the future of autonomous, green, and digital solutions in mobile working machines, with a strong emphasis on AI, robotics, and mechanical engineering.

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.