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Field
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, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
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computer science including AI, machine learning, computer vision, graphics and visualization, systems, distributed algorithms, and scientific and biomedical computing. Research in the department is and has been
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and application architectures with implementations of massively distributed embedded systems that interact with each other and their environment to enable secure, goal-driven, autonomous and evolvable
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departmental algorithms, the Scheduler critically evaluates the nature and urgency of scheduling requests to provide comprehensive clinical ambulatory scheduling for providers within the department specialty
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. The HEXAPIC project aims to develop a novel high-performance Particle-In-Cell (PIC) code for plasma physics simulations, leveraging the capabilities of exascale computing systems. By optimizing PIC algorithms
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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socially just energy supply system based on renewable energies. We contribute to this with our research focus on energy supply, energy distribution, energy storage and energy use. Through outstanding
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socially just energy supply system based on renewable energies. We contribute to this with our research focus on energy supply, energy distribution, energy storage and energy use. Through outstanding
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distributed tasks such as inspection of a big geographic area for fires is an important objective of this project. The project aims are to: 1) provide methodological contributions towards intelligent sensing
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out research on distributed acoustic sensing (DAS) data analysis and participate in continued development on the inclusion of DAS data within the network monitoring systems. We seek applicants who like