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numerical modelling, simulation, optimization, control, or engineering-data analysis. Good programming skills in Python, MATLAB/Simulink, or a comparable scientific computing environment. A fundamental
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related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with deep learning, computer vision, medical image analysis
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perception, optimization, or control will be an advantage. The candidate should be comfortable with scientific programming, for example in Python and common machine-learning frameworks such as PyTorch
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-driven modelling. Experience with numerical modelling, simulation, optimization, control, or engineering-data analysis. Good programming skills in Python, MATLAB/Simulink, or a comparable scientific
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or a related field; strong academic results and foundations in machine learning, linear algebra, probability and optimisation; and strong Python and PyTorch (or comparable framework) skills. Only
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in Python with the ability to implement and prototype research ideas. • A mathematical foundation to support the design and analysis of algorithms. • Curiosity, motivation, and strong
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and fatigue analysis. Experience in coding (e.g., Python) and in the use of structural analysis software (e.g., Abaqus, OpenSees) is desirable. Familiarity with virtual sensing techniques, state
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sensing, AI-based methods and data-driven hydrological models, as well as experience in operationalising real-time hydrological systems and programming in, for example, Python. In addition, you are expected
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environments, such as MATLAB, Python or similar tools, will support your work in the project. Knowledge of Power-to-X, electrolysis, renewable fuels, process integration or energy storage will be advantageous
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learning, computing, data science, biomedical engineering, or a related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with