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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
(RMM-VLE) based on DTCS and real-time IoT/sensor data Assessment of pedagogical value in user experience studies on enhancing learning experiences (e.g., engagement, motivation, and knowledge retention
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
Virtual Learning Environment (RMM-VLE) based on DTCS and real-time IoT/sensor data Assessment of pedagogical value in user experience studies on enhancing learning experiences (e.g., engagement, motivation
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electroencephalogram (EEG) and potentially other modalities (e.g., functional near-infrared spectroscopy (fNIRS)) to improve decoding accuracy and user-specific adaptation. Key research areas include: EEG signal
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consumers. You'll gain deep interdisciplinary experience—combining multiple data layers and approaches including bioinformatics, machine learning, food safety management, regulatory science, genomics and user
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/sensor data Pedagogical value and user experience studies on enhancing learning experiences (e.g., engagement, moti-vation, and knowledge retention) through immersive and interactive VLE Scientific
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bionic limbs in health). This requires comprehensive integration of many data sources coming from the user, robot, and environment. This challenge can be addressed only using advanced AI. This lab will
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researcher excited about working on the cutting edge of AI/Neuromorphic and user interface design? We'd love to hear from you! Research area and project description A Brain-Computer Interface (BCI) decodes
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Center (CoaST). These facilities are now equipped with modern graphical user interfaces, unified communication protocols, and structured data pipelines that collect and store experimental data in dedicated
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prior experience in at least three of the following areas: Python programming Develop LLM-based tools to automate data connector generation for data ingestion. Design and implement a multi-layered storage
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. Experience in modeling biological processes. Experience in use of process simulation tools such as Matlab, Aquasim, Superpro Designer or similar. Expertise within fermentation technology and/or gas