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candidates within Modelling Strength and Failure in Recycled AluminiumAlloys funded through the Centre for Research-based Innovation SFI FAST – Future Aluminium Structures. The positions are linked
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. Digital twin technologies offer a promising approach for modelling and monitoring such complex systems. However, the ongoing energy transition also introduces significant uncertainty due to fluctuating
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modelling and monitoring such complex systems. However, the ongoing energy transition also introduces significant uncertainty due to fluctuating renewable generation, dynamic demand, and increasingly complex
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and fundamental knowledge in mathematical modeling of robotic systems, mechanics, kinematics and dynamics, control Solid background or experience in programming in C++, MATLAB or similar platforms
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UiA-CERN PhD Position in Multi-robot Mapping and Environmental Data Sharing - Uncertain Environments
) or higher in the final MSc project is also required. Strong analytical skills and fundamental knowledge in mathematical modeling of robotic systems, mechanics, kinematics and dynamics, control, communication
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the Telemark Canal , focusing on digital twin-based preparedness modelling for cultural heritage infrastructure. The primary objective of the position is to complete a doctoral education leading to a PhD degree
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on the combination of Reinforcement Learning (RL) and Model Predictive Control (MPC). It will build up upon the work done at ITK on the topic. Several research focuses are considered: verification pathways in RLMPC
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with over 60 companies. The research will focus on the combination of Reinforcement Learning (RL) and Model Predictive Control (MPC). It will build up upon the work done at ITK on the topic. Several
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analysis. Specifically, the project will: Develop novel, modular statistical solvers to integrate domain-specific knowledge directly into latent variable models. Account for spatial structures, physical laws
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9th March 2026 Languages English English English The Department of Electric Energy has a vacancy for a PhD Candidate in Multi-market modelling of power systems with large amounts of wind power Apply