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collaboration. Our faculty uniquely integrates perspectives from technology, information, business, and human behavior. Our multidisciplinary approach is at the heart of everything we do – from teaching to
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the digital future through research, education, and close collaboration. Our faculty uniquely integrates perspectives from technology, information, business, and human behavior. Our multidisciplinary approach
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where needed. You will join an international, collaborative team with access to excellent core facilities and computational infrastructure in Helsinki. The positions We are hiring two postdoctoral
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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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a Finland-Japan special collaboration scheme with partners from Japan including University of Tokyo, Kyoto University, Yamagata University, and National Astronomical Observatory of Japan. The project
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inequalities and Sobolev-type spaces (with Hytönen and/or Korte), 3. Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic
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collaborate effectively in large inter-disciplinary teams from different cultural backgrounds Strong ability to support Masters-level teaching in the human dimensions of natural resource management Strong
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-authored publications submitted to suitable venues, which will be determined collaboratively with the PI. QUALIFICATIONS The appointee must hold a doctoral degree in computer science, digital humanities or a
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of Humanities and Social Sciences - a pioneer in research and education. The Faculty of Humanities and Social Sciences at the University of Jyväskylä is a multidisciplinary scientific and learning community, with
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Center (ACCC), a Finnish Flagship (website) . The recruited Postdoctoral Researcher is expected to work closely with other research groups in the ACE-Forest consortium and with international collaborators