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autonomous robotic systems; •Proven knowledge of control architectures for cognitive robotic systems (preferably based on nonlinear dynamical systems in the form of neural dynamic fields); •Experience in
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and dynamical mean-field-theory levels, metal-insulator and structural phase transitions, quantum critical points, nonlinear and anomalous responses, optical traps, quantum computation and information
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Research theme: Control Engineering, Robotics How to apply: https://uom.link/pgr-apply-2425 UK only This 3.5-year PhD studentship is open to Home (UK) applicants. The successful candidate will
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FCT code 2023.17217.ICDT and DOI https://doi.org/10.54499/2023.17217.ICDT . , funded by COMPETE 2030 by Portugal 2030, and by the European Union, financial support from national funds/OE through
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implement new nonlinear iterative solvers, with the goal of exploiting models of various complexity, ranging from high-performance computing, via reduced-order models to data-driven (machine-learned
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for applicants from outside of EU/ EEA countries and exemptions from the requirements: https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 Grade requirements: The norm is as follows
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such as spectrally controlled reflectivity and transmission, down conversion, light trapping and light extraction, nonlinear effects, and solar cells. The work involves electromagnetic modeling
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statistics of mean and extreme wind events over the Baltic Sea region. Tellus A, 67, 29073. https://doi.org/10.3402/tellusa.v67.29073 Björkqvist, J.-V., Lukas, I., Alari, V., van Vledder, P.G., Hulst, S
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the final exam. Desired qualifications: Background in probability theory and Monte Carlo methods, and familiarity with stochastic processes. Strong background in hydrodynamic, nonlinear and stochastic wave
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, analytical methods, and/or control of nonlinear MIMO mechatronic systems. Strong experience in experimental validation using state-of-the-art measurement systems. A robust national and international network