36 complex-network-"UCL"-"UCL" Postdoctoral positions at Oak Ridge National Laboratory
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or integrating control algorithms into physical testbeds Knowledge of predictive maintenance methods and anomaly detection techniques for complex systems Experience with sensor networks, IoT platforms, or real
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of complex biosystems. The successful candidate will also contribute to efforts that bridge molecular, cellular, and systems-level modeling, with growing relevance to emerging paradigms such as whole-cell
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incorporated into complex microelectronic and optoelectronic architectures, with particular emphasis on interfaces between two-dimensional and conventional semiconductor materials. This position resides in
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sciences to enable quantum computers, devices, and networked systems. It develops community applications, data assets, and technologies and provides assurance to build knowledge and impact in novel, crosscut
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quantification of radioactive complexes. As a member of our research team, you will take a leading role in the design, synthesis, characterization, and evaluation of novel chelation platforms for medically
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Peatland Responses Under Changing Environments) experiment and other DOE-supported observational networks. Major Duties/Responsibilities: Develop, implement, and test new and improved process representations
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Peatland Responses Under Changing Environments) experiment and other DOE-supported observational networks. Major Duties/Responsibilities: Develop, implement, and test new and improved process representations
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complex magnets via interpretable machine-learning models, and develop improved AI models that can accelerate prediction of new synthesizable magnet candidates with high energy density and critical
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interact closely with industry partners. These engagements will play a vital role in ensuring success of programs and the adoption by project sponsors, and in developing your network across academia and
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models of gas transport and process behavior in industrial systems Collaborate with a team of scientists from across the national laboratory complex on modeling efforts Extend process flow modeling across