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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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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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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
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for a PhD/Postdoc position within the Control Systems Technology section at the Department of Mechanical Engineering. This project focuses on developing model predictive control (MPC) algorithms
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of research projects in a variety of domains. Under the onslaught of ever-larger amounts of data and to take advantage of improvements in machine algorithms, the Zooniverse team has built and implemented
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timing distribution. Experience with PCB schematic capture & layout tools such as Cadence, Mentor Graphics, Altium, or KiCAD. Experience implementing DSP algorithms on FPGAs. Experience with Vivado High
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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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detailed dynamical models of galaxies and stellar clusters to infer the distribution of luminous and dark matter as well as to uncover the formation history of these stellar systems. Ready to be part of our
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management expertise to support a workgroup of researchers using satellite algorithm-based models to track marine environmental conditions, generate habitat distribution maps, and produce forecasts
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and financial planning tools; this includes modeling new algorithms, creating functional specifications, and testing and/or validating new financial planning tools. Collaborate with other members