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design of instrument performance. key words mathematical modeling; differential equations; simulation; perturbation methods; optimization Eligibility citizenship Open to U.S. citizens level Open to
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of microbial communities. · Apply active learning strategies to optimize experimental design. · Integrate genetic and functional data using high-throughput experimental datasets. · Collaborate
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implementations on computers. We are particularly interested in nonlinear optimization problems, which involve computationally intensive function evaluations. Such problems are ubiquitous; they arise in simulations
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. • Characterisation of cooperation amongst elements of a network in terms of robustness and optimality. • Synthesis and design of nonlinear distributed controllers. • Data-driven control in a nonlinear setting. This
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systems coupling sensing, internal regulation, and body dynamics. Inspired by nonlinear physics, we will investigate normal forms (i.e., universal weakly nonlinear descriptions) and determine when such
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accepted all year round Details Model predictive control (MPC) is a popular advanced control technique that solves a constrained optimal control problem, on-line, at each sampling instant. The first control
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, the parameter adjustments are usually performed in a brute-force manner, without considerations of nonlinear coupling between multiple parameters. As a result, the models (that reproduce the data that they were
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fields like communication, energy, health, and mobility. The focus in the RF Power Lab is on applications with output powers in the range of 5...200 W in the microwave range up to 40 GHz. We work on novel
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optimization, including integer, nonlinear, and combinatorial optimization; global and non-convex optimization; machine learning for optimization; explainable artificial intelligence; heuristic and metaheuristic