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tackles fundamental challenges in multimodal representation learning by developing novel approaches to align distinct embedding spaces from speech and sign language modalities. Sign languages encode
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to make viable trading decisions under high price volatility. This PhD position focuses on designing, developing, and evaluating self-learning energy trading algorithms that are able to cope with
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of machine learning frameworks Your research will include using models and codes to investigate the optimized design, integration, and intelligent operation of thermal energy storage systems in industrial
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(SELECTED TASKS) From requirements analysis to conceptual design and final creation and validation of Runtime Multimodal Multiplayer Virtual Learning Environment (RMM-VLE) based on DTCS and real-time IoT
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Vapour fed electrolysers can generate green hydrogen even from impure water sources. However, water vapour itself contains gaseous impurities. During this 3-year PhD, we will design and characterise
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focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data
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characterization and fingerprinting. design and execute experiments to trap single proteins. perform in-depth data analysis and pattern recognition to extract protein properties from electrical current reads
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. Fe, S) on CNT purity and structure. Evaluate CNTs as conductive additives in standard Li-ion battery electrodes. Apply AI/machine learning to optimise experimental design and growth parameters
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well as observer studies, screening, radiation dosimetry, along with the design and performance of patient trials. Radboudumc Welcome to Radboud university medical center (Radboudumc), where scientific breakthroughs
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generation of Doctoral Candidates (DCs) capable of tackling these challenges through cutting-edge interdisciplinary research and innovation. REUNATECH brings together leading universities, research institutes