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Distributed, robust and adaptive model predictive control (MPC) School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr P Trodden Application Deadline: Applications
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Laboratory, Materials Measurement Science Division opportunity location 50.64.31.C0344 Gaithersburg, MD NIST only participates in the February and August reviews. Advisers name email phone Thomas P Forbes
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P Yang, Dr Tong Liu Application Deadline: 15 January 2026 Details A fully funded PhD opportunity to participate in the world-leading research undertaken by the EPSRC Doctoral Landscape Award
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of Medicine-Phoenix Location Greater Phoenix Area Address 475 N. 5th St., Phoenix, AZ 85004 USA Position Highlights The University of Arizona College of Medicine – Phoenix (COM-P) is seeking a highly motivated
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NIST only participates in the February and August reviews. We are developing machine learning algorithms to accelerate the discovery and optimization of advanced materials. These new algorithms form
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systems. This work will specifically focus on combining ML algorithms with classical data analysis and control techniques to develop robust in situ (i.e., in real-time, during the operating experiment
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challenging data problem. Weak signals from collisions of compact objects can be dug out of noisy time series because we understand what the signal should look like, and can therefore use simple algorithms
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distributions. We wish to represent the biological networks into proper formats, e.g., vector representations, so that existing machine learning algorithms (e.g., support vector machines) can readily be used
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extensive measurement capabilities, CMOS circuit design work for foundry tape-out, and theoretical work developing new algorithms and architectures that leverage the low-energy, high-speed properties
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Constrained control and set invariance School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr P Trodden Application Deadline: Applications accepted all year round