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environment. Join us in shaping the future! The position is part of Profi 8 research “Transformation of urban systems” funded by the Research Council of Finland. The work aims at modeling carbon flows
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mechanisms involved in the new multi-target therapeutic strategies, both in 2D and 3D cell cultures and in an animal model of cancer. Experience in these areas will be valued, as well as publications with a
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learning models that can be utilised by health services to make real-time, data-informed clinical decisions in youth mental health care. Your key responsibilities will be to: recruiting study participants
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. The research group is seeking a talented Doctoral Researcher in nonlinear systems and control with strong interest in nonlinear stability theory, modeling & identification, optimal control, certifiably safe
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stability theory, modeling & identification, optimal control, certifiably safe & robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven
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data science methods to build explainable and integrated machine learning models that can be utilised by health services to make real-time, data-informed clinical decisions in youth mental health care
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the matching of models to real-world targets, and that a better understanding of this class of methods will provide insights for planning and evaluating translational research. This project will be primarily
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a postdoctoral scholar to lead collaborative efforts among researchers at the University of Utah and UC San Diego in developing and applying methods in predictive and causal modeling of complex
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of large datasets, for example: to integrate biological/genomic data with biogeochemical measurements, biogeographic, phylogenomic, comparative, time series (community or population) modelling/analyses
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highly integrated, multidisciplinary approach involving enzyme kinetics, molecular modeling, and biological testing to discover, design, and develop new therapeutics. This position is also anticipated