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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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capable of breakthroughs. The research will mix state of the art numerical skills with analytic understanding. Your task is to predict new classes of materials that have not been considered before, beyond
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-effectively predicting the rate of massively multicomponent organic, or organic-enhanced, new-particle formation in the atmosphere. We will combine our molecular-level model development with machine learning
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particle formation for atmospherically relevant molecules. ORCTOOL (Organic Cluster Tools) aims to create a toolbox for understanding and cost-effectively predicting the rate of massively multicomponent
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how natural selection shapes sex-specific immune strategies. The goal is to generate quantitative predictions testable against empirical data from diverse ecological contexts. We use methods from
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ecology predictions and empirical data on the evolution of sex-specific differences in immunity and life history traits. As we intend to conduct interviews also during the application period, we appreciate
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, communication, social sciences and philosophy. The humanities play a significant role predicting global developmental trends and social changes as well as in meeting societal challenges and managing large masses
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quantitative predictions testable against empirical data from diverse ecological contexts. We use methods from theoretical evolutionary biology, including optimal control theory, life history modelling, adaptive
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with various methods. By integrating the findings with archaeological knowledge, the goal is to elucidate bacterial genetic evolution that was shaped by human influence and make predictions to the future
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knowledge, the goal is to elucidate bacterial genetic evolution that was shaped by human influence and make predictions to the future. The work provides the possibility to develop skills in microbiology, data