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simulation of algorithms for detecting intermittent faults in compensated networks. Identification and testing of conditions for selective protection of intermittent faults in meshed and radial networks
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domains. The successful candidate will: Develop algorithms to model team performance based on interpersonal (e.g., monitoring, communication) and cognitive (e.g., shared mental models) processes. Design an
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available under the following conditions: OBJECTIVES | FUNCTIONS Development and evaluation of machine unlearning algorithms for speech foundation models, including: - Selection and preparation of models and
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learning methods to digital pathology Development of deep learning algorithms for the computational analysis of whole-slide images. The objective is to identify relevant biological features and to perform
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architectures for explainable dual-process computation Design and development of deep neural network architectures and algorithms for the implementation of dual process computation approaches that improve
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factors: Preference will be given to candidates with suitable scientific and professional curriculum such as: Cloud Computing, Operating Systems, Distributed Systems, Virtualization EVALUATION CRITERIA
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collection, processing, and hospital distribution to meet demand while minimizing waste. In this context, two major objectives are identified: (i) to assess nation-wide changes to blood donation and demand