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and Sobolev-type spaces (with Hytönen and/or Korte), Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic game
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structures unavailable elsewhere. Your role and goals The successful candidate is expected to lead the experimental effort with a team of PhD and master’s students and collaborate closely with theorists in
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
to develop machine learning-enabled approaches for predictive modelling and state estimation for fundamental applications within physical sciences. Your role The main research responsibilities involve building
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
from all backgrounds to join our community. The Nonlinear Systems and Control group is seeking a talented and ambitious Postdoctoral Researcher to develop machine learning-enabled approaches
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also have a chance to instruct Doctoral researchers and Master thesis candidates and develop towards a more independent position. Background and expertise We are looking for candidates who understand