Publisher
source

Gokhan Alcan

4 months ago

MSCA Doctoral Researcher (Predictive Models for Contact-Rich Construction Tasks) Tampere University in Finland

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Expired

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Country

Finland

University

University of Tampere

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Where to contact

Official Email

Keywords

Computer Science
Mechanical Engineering
Mathematics
Algorithm Design
Predictive Modeling
Artificial Intelligence
Simulation Training
Reinforcement Learning
Optimal Control
Building Automation
Model Predictive Control
Rotating Machinery
Robotics
Machine learning

About this position

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.

Funding details

Available

What's required

Applicants must have a Master of Science (MSc) diploma in relevant engineering disciplines or applied mathematics and be eligible for enrollment in the Tampere University Doctoral Program. Candidates must not have been awarded a doctoral degree and must comply with the MSCA Mobility Rule, meaning they must not have resided or carried out their main activity in Finland for more than 12 months in the 3 years prior to recruitment. Proficiency in written and spoken English is mandatory, and a language certificate may be requested. Experience with machine learning, deep learning, reinforcement learning, simulation environments, and optimal control is appreciated. The candidate must also comply with Tampere University's and Finland's employment requirements.

How to apply

Submit your application through the Tampere University online recruitment system (LAURA portal) by November 16, 2025. Required documents include certified copies of degree certificates, official English translations, CV (preferably Europass format), motivation letter, and proof of residence. Early applications are encouraged as interviews may begin during the application period.

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