29 machine-learning-modeling-"LIST"-"CEA-Saclay"-"Humboldt-Stiftung-Foundation" positions at Technical University of Denmark
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(e.g., Kalman Filter) or Machine Learning models. These tools will be integrated with physics-based models of environmental loading (waves and wind) to enhance the accuracy and robustness
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human
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computationally efficient numerical structural models. To support the condition (state) assessment, the project will also explore the use of advanced estimators (e.g., Kalman Filter) or Machine Learning models
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, TESPy, or similar libraries. Strong programming skills in Python or MATLAB, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit
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within the broad topics of modelling tool-workpiece interaction in mechanical material removal processes, zero-defect manufacturing, machining system performance characterization as well as on-machine and
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-of-concept of such systems and have a practical understanding of: Signal processing algorithms, Security and Privacy Antennas and RF sensing Machine learning for communications systems Integrated Sensing and
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digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design
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externalities of transport. The division is interdisciplinary with scholars originating from transportation engineering, economics, psychology, computer science, social data science, machine learning, mathematics