12 condition-monitoring-machine-learning Postdoctoral positions at University of California, Merced
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at the intersection of scientific computing and machine learning. At a high level, the project is to build neural network models of potentials that appear in Hamiltonians for time-dependent quantum systems. The postdoc
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scholar to conduct research at the intersection of robotics, controls, and machine learning. The successful candidate will help shape next-generation approaches for autonomous multi-robot systems
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Curriculum Vitae - Your most recently updated C.V. Cover Letter Authorization to Release Information Form - As a condition of employment, the finalist will be required to disclose if they are subject to
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in Agriculture • Machine learning models for pest and disease prediction • Crop classification using multispectral imagery • Digital twin models for farm simulation and management • Collaborate with
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Information Form - As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining
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of Research Authorization to Release Information Form - As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within
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systems, machine learning, and control theory. Experimentally validating these methods through field experiments. In addition to conducting research, the Postdoctoral Scholar will collaborate closely with
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excellent opportunity to work in the development of external relationships and to engage in industry-university partnerships at the cutting edge of engineering, computer and data science, technology, natural
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-reviewed scientific journals. Application Requirements Document requirements Curriculum Vitae - Your most recently updated C.V. Cover Letter Authorization to Release Information Form - As a condition of
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. • Experimentation and Data Collection, conduct field experiments to evaluate the performance of the LoRa network under various agricultural conditions. Collect and analyze data from deployed sensors to assess network