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Field
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(AIED) and Educational Data Mining (EDM) projects with Professor Kalina Yacef. These projects explore how multimodal data from online platforms and sensor-based environments can be harnessed to enhance
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work will be organized around the following areas: 1. Bee detection and tracking: Development of computer vision algorithms to identify and track each bee from high-resolution images, while
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engineering and proficiency in information technology, with particular emphasis on computer networks, network system security, the Internet of Things, sensor networks, Windows and Linux operating systems, web
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underlying pain and distressing symptoms in people who are no longer able to explain their suffering. The project will combine traditional assessment scales with sensor-based measurements, with novel analyses
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simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power consumption and
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National Laboratory (ORNL). The NEEM Group focuses on pushing the limitations of materials, sensors, and experiments through technology development, advanced instrumentation, irradiation experiments, and
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will work in a group with other students and take on specific tasks. The aim is to analyse the robot's capabilities and to implement algorithms that enable the robot to be used sensibly in applications
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will work in a group with other students and take on specific tasks. The aim is to analyse the robot's capabilities and to implement algorithms that enable the robot to be used sensibly in applications
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(HPC) best practices, advanced mathematical research into novel algorithms, and the utilization of machine learning techniques for code acceleration and the development of reduced-order "surrogate
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, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power