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Field
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continuously learn from data in a distributed way. Coupling of new theory with effective implementation strategies have the potential to make a lasting impact on building efficiency through sustainable
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and distributing high quality content to promote the Hub’s activities and impact. This post holder will develop and implement effective communications and engagement strategies that align with the Hub’s
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Required Skills: Current or planned MS or PhD student at the University in CS or related field. Solid background and working knowledge of computer science fundamentals including algorithms, data structures
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.), distributed computing (cloud computing, microservices, etc.), Dev(Sec)Ops, software engineering (software product lines), human factors in security and privacy, post-quantum and embedded cryptography, and
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/Fortran) Shared and distributed memory programming tools (e.g. OpenMP, MPI) Accelerator programming (e.g. CUDA, OpenCL, SYCL) Machine Learning libraries such as Tensorflow or PyTorch Serial and parallel
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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-scaled CMOS models. Advanced algorithms and architectures need investigation of power-consumption trade-offs. For instance, digital predistortion (DPD) can enhance power amplifier efficiency but
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to integrate data to realize collective-distributed perception? 3) How to buld reliable navigation solution based on limited sensor data The study goal is to carry out high-quality research in this domain
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research areas encompass the synthesis of novel converter topologies, development of specialized control and protection algorithms, integration of cutting-edge components, and formulation of design
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programs for distribution to the research community as well as management of datasets, including sequencing data. Job Description Job Responsibilities Develop novel algorithms to analyze next generation