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topics: Predictive Coding of Music, led by Peter Vuust (PI, Director) Multimodal Theme, led by Boris Kleber Music Interactions, led by Peter Keller Meaning of Music, led by Elvira Brattico (PI) and Morten
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to integrate various structural biology data (NMR, SAXS, FRET, EPR) as well as computational models and simulations to create and interpret conformational ensembles of disordered protein regions, with the goal
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to protein engineering and molecular cloning, Experienced in bioinformatic genome analysis and computational tools related to protein structure analysis and prediction, Sufficient expertise in standard
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. The research to be addressed AI has been applied to Software Engineering for some time, and in areas such as software effort estimation, defect prediction, and project management in general. And more recently
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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environments. Your key responsibilities will include: Developing hydrological models to predict recharge zones using remote sensing and in-situ data. Integrating soil moisture maps, digital elevation models, and
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outputs. Collaborating with geophysical teams to refine RS-based predictions with subsurface imaging data. Participating in international fieldwork campaigns, stakeholder workshops, and project coordination