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on developing new cement formulations and characterization techniques. For algorithms and software there will also be the opportunity to work with the team behind the Core Imaging Library (CIL) and contribute
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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process modelling, experimental data, model parameters and modelling approaches in order to optimize design, analysis and operation of complete capture processes. The goal of the project is to develop
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techniques for integrating such solutions into modern SDV middleware. Responsibilities: Conduct research in runtime analysis and reconfiguration of in-vehicle TSN networks. Develop algorithms and prototypes
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reaction evolution mechanisms for magnesium-based binders, leveraging state-of-the-art experimentation and numerical modelling tools. This position is part of the prestigious Villum Synergy project
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statistical and machine learning techniques for dynamic energy system modelling Develop advanced optimization algorithms for building energy management and control (e.g., MPC, RL) Develop and evaluate digital
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research environment focusing on integrating multi-source data and developing novel algorithms to address the challenges posed by global environmental change. You will focus on integrating experiments, field