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to conduct research in the areas of safety-critical control theory and machine learning. The role will focus on combining new theory or method in nonlinear system control and state-of-the-art machine learning
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nonlinear MEMS-based oscillators driven by storage-ring radio-frequency (RF) signals to enable advanced manipulation of X-ray pulses. Background information on the project can be found in the publications
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emphasis on standard and non standard finite element methods with applications to wave propagation problems and nonlinear reaction-diffusion problems. Further information about our research area and about
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the contract. More information is available on: Workplan and the objectives to achieve: The work to be carried out consists of the development and experimental validation of nonlinear and hybrid control
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finite element methods with applications to wave propagation problems and nonlinear reaction-diffusion problems. Further information about our research area and about our team can be found on our homepage
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emphasis on standard and non standard finite element methods with applications to wave propagation problems and nonlinear reaction-diffusion problems. Further information about our research area and about
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Biosciences, ETH Zurich develops experimental methods for measuring and controlling electronic dynamics in molecules on attosecond time scales, during chemical reactions and in the liquid phase. Project
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the Faculty Statistician, including: Longitudinal & repeated-measures studies (e.g., linear/nonlinear mixed-effects models, GEE, repeated-measures ANOVA) Survival & time-to-event analyses (e.g., Cox
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the goal to obtain more in-depth process understanding and develop automated control strategies for single cell microbial suspension cultures. Currently, the team is working on liquid- and gas-phase
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., R, Python, Julia), preferably including scientific software development. Knowledge of ecological statistics (frequentist and/or Bayesian), particularly spatial statistics and nonlinear models