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and control of windfarms For this position the research activity is expected to develop new methods in robust and physics-informed machine learning, reduced-order modelling, data-driven nonlinear model
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). In this role, you will perform computational studies aimed at better understanding of photochemically driven processes to control ligand binding and release, and pH modulation using photoacids and
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Control engineering (experience with nonlinear systems is a plus) Machine learning and deep learning in context of physical systems Programming skills are required, with Python experience preferred. A good
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at the intersection of control theory and machine intelligence. Methodologies of interest include: Robot modelling, Nonlinear and Optimal control, Reinforcement learning, and Data-driven modeling and control. The Post
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, Electric vehicles chargers, or nonlinear loads Experience in hardware-in-the-loop testbeds and digital twin creation Experience with SEL RTAC 3555 or similar Experience in advanced microgrid controls such as
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developing adaptive numerical schemes powered by advanced nonlinear approximations—like Gaussian mixtures and neural networks. The key challenge? Designing robust and stable numerical schemes that remain
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progress in optogenetics have allowed to activate neuronal circuits precisely. Here we will use these tools to control the cochlear output and activate optogenetically cochlear hair cells in vivo. Optical
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numerical solution a serious computational challenge. This project aims to tackle that head-on by developing adaptive numerical schemes powered by advanced nonlinear approximations—like Gaussian mixtures and
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for the analysis of nonlinear phenomena in adaptive dynamical networks with applications to restoration ecology. Adaptive dynamical networks are mathematical models of coupled systems where both the systems
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potential applications. In particular, we focus on evolutionary prediction: can we use a deeper understanding of evolvability to predict and, potentially, control evolutionary processes? Read more about our