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hardware modification. The AI will learn and adapt the realms of the combustion modes and fine tune the performance for each while the engine is operated. Self-tuning, adaptive, control algorithms will be
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developing 3D vision algorithms for object detection, recognition, and scene understanding to support planning and task execution in dynamic environments. Publishing research findings in leading international
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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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meetings Potentially participate in Arctic field campaigns Be working with large data sets and developing algorithms. You should be highly motivated, self-driven, and possess strong work ethics, team spirit
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data Design algorithms for correlating low-level events into process-level attack models Contribute to joint framework development with TU/e on continual learning Collaborate with industry partners
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will focus on developing a bioinspired, AI-driven BCI system that enables intuitive and adaptive control of a wearable wrist-hand exoskeleton for stroke rehabilitation. The system will integrate
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will take advanced courses to build and deepen your skills, implement and evaluate algorithms, and develop your ability to write and present scientific work. We are a supportive team that will welcome
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these frameworks to develop specific formulations and solution algorithms for the design of congestion pricing schemes using classical transport models and quantify the equity-efficiency trade-offs for congestion
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the section that aims to develop the next generation of scientists trained in bioinformatics, AI/ML and data science who have a deep understanding of experimental biology as well. Responsibilities As a PhD