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scenarios for achieving a low-carbon society in 2050. A key ambition of the project is to support scenario-based planning and backcasting. Rather than predicting a single future, the modelling framework
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foundational methods for integrating single-cell and clinical transcriptomes; and train, fine-tune, and validate deep learning models using multi-omics and imaging data to predict clinical outcomes such as
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Future robots must perceive, predict, communicate, and decide reliably in complex, human–robot shared environments. The Mobile Robotics (https://www.aalto.fi/en/department-of-electrical-engineering
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predict interaction effects. Unlike robot-specific neural network models, the proposed approach aims to learn a universal representation of local interactions (fluid-structure, robot-robot, robot-object
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estimation, and performance prediction. Build computationally efficient models suitable for monitoring, performance prediction, optimization, and control, and evaluate their accuracy, robustness, computational
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properties predicted by Virtual-Coater™ can be translated into meaningful input parameters for battery modelling platforms. The ultimate objective is to establish a predictive modelling workflow capable
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models and monitoring data to assess its current structural state and predict its remaining lifetime. This will enable the condition of welded structures to be monitored throughout their service life
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devices, building a software-supported framework to predict and optimize laser-material interactions, energy transfer, and resulting micro-scaled features during drilling and shaping, and modelling of beam
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learning-based model predictive control (MPC) algorithms for multi-agent multirotor drone navigation around vessels in maritime environments. The role will focus on integrating multirotor crash predictions
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of relevant experience Ability to use statistical analysis, simulations, predictive modeling, or other methods to analyze information and develop solutions that support the university's mission Advanced