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unified computational framework capable of capturing complex interactions in organic matter for use across different research fields. Positions 2-3: These positions include a fair amount of method
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. First, efficient and scalable training procedure are still needed, irrespective of whether the training is done off-line on a traditional GPU-based architecture, on neuromorphic hardware. Second
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and run it efficiently on different hardware architectures. For example, Google has built TensorFlow, a framework for deep learning allowing users to run deep learning on multiple hardware architectures
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of neuromorphic systems for different types of onboard sensing and processing tasks in the space environment. Your research will be guided by your own expert judgement and insight into current trends in AI hardware
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
techniques and approaches to difference image analysis, survey-scale photometric calibration and detrending, periodicity searches, and/or other areas. A negotiable fraction of this role is reserved
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
techniques and approaches to difference image analysis, survey-scale photometric calibration and detrending, periodicity searches, and/or other areas. A negotiable fraction of this role is reserved
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challenge the status quo. At Jane Street, you will work alongside a tight-knit team, utilizing petabytes of data, our computing cluster with hundreds of thousands of cores, and our growing GPU cluster
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profiler . Experience with GPUs is a bonus. Of course, you need fluency in written and spoken English to communicate your ideas in this interdisciplinary project. Note that we expect from candidates either