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Field
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modelling. MISSION You will actively contribute to the development and evaluation of new hybrid computational method to predict biological tissue deformation with subject-specific material properties
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Geospatial analysis, machine learning, and predictive modelling, Have a good command of programming tools such as R packages, Phyton, and other programming languages Publications in the field Excellent
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University Abu Dhabi invites applicants to apply for the open Post-doctoral Associate position to perform primarily research on Reinforcement Learning, and/or Optimal Control, and/or Model Predictive Control
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to work on the use of hyperspectral data to explain and predict soil functions and communities in European mountains. We are looking for a candidate who has a very good command of artificial intelligence
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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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effectiveness and toxicity of the treatments. Other duties: Develop and validate cancer risk prediction models using deep neural networks based on semistructured data. Develop and validate learning strategies
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fields). Strong quantitative skills and demonstrated expertise in predictive modeling and advanced computational methods (e.g., Multilevel Vector Autoregressive Models, Dynamic Structural Equation
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environment. Development of models to diagnose and predict battery performance and ageing. Participation in national and international research projects related with energy storage and its integration in
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development of new computational and mathematical models to quantify and predict infectious disease risk, particularly for identifying high risk individuals and groups. The PDRA will translate conceptual
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predict the location of resources more accurately, it is necessary to model these processes jointly at the basin scale. However, directly solving geochemical equations is computationally expensive and