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23:43:42, 7 November 2019 +
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December 1, 2019 +
'''POSITION:''' PhD Student
THE OCCASION … '''POSITION:''' PhD Student</br></br>THE OCCASION OF COVERAGE: Project: RESEARCH AND DEVELOPMENT OF METHODOLOGIES AND TOOLS FOR IMPROVING REAL-TIME FLOOD FORECASTING CAPABILITIES. VALERIA</br></br>'''ENTITY OF ADMINISTRATIVE DEPENDENCY:''' Fundación Instituto de Hidráulica Ambiental de Cantabria</br></br>'''GENERAL MISSION:''' Conception or creation of new theories, knowledge, products and techniques performed on a doctoral thesis.</br></br>'''GENERAL TASKS'''<br></br>Elaborate, under the supervision of the thesis advisor, his own doctoral thesis that allows for the broadening of scientific knowledge, creating new theories or modifying existing ones.</br>Collaborate in the area of study, under the supervision of the thesis advisor or the project manager, and assessment of a given project</br></br></br>'''SPECIFIC TASKS'''<br></br>The goal of the project es to improve hydrological predictions and uncertainty estimation. The specific topic/forus will be defined during your doctoral thesis. The thesis should broaden scientific knowledge, present new methods, or improve the existing ones. Potential approaches are:</br>* Probabilistic stream fbw predictions using erroroorrection models and data assimilation techniques. Compare traditional techniques for model errors correction, such as ARMA models, with more advanced techniques for state and parameters updating such us Ensemble Kalman Filler and Regularized Particles Filler. Identify the mai’I source or uncertainty. Case study will use conceptual hydrological models and historical data from 2-3 selected catchments.</br>* Predictions using purely data-driven hydrological models. For example recurren! artificial neural networks (specifically, Long Short Term Memory Neural Networks). Quantify the aoo.iracy and robustness of the predictions to compare advantages and disadvantages of replacing the hydrological model by a data-driven model investigate approaches to predict the uncertainty of da1a driven hydrological models.</br></br>The research project involves hydrology, statistics and maths</br>The works is performed in close collaboration with the thesis advisor.</br>We offer flexible freedom to explore new topics, a good international network and a close interaction with recognized experts.</br>Scientific collaboration with related pronec1s and publication of scientific results are part of the program_</br></br>'''REMUNERATION:''' 16,422 EUR/YEAR gross salary (12 payments)</br></br>'''DEADLINE FOR APPLICATION:''' 1st December, 2019</br></br>'''EXPECTED DATE OF JOINING:''' 3rd January, 2019</br></br>Please, see the following link for further details:</br>http://www.ihcantabria.com/en/fundacionih/item/1652-convocatoria-para-la-seleccion-de-personal-n-conv-fihac-10-2019/1652-convocatoria-para-la-seleccion-de-personal-n-conv-fihac-10-2019ria-para-la-seleccion-de-personal-n-conv-fihac-10-2019
PhD opportunity +
PhD student position on research and development of methodologies and tools for improving real-time flood forecasting capabilities +
Instituto de Hidráulica Ambiental de Cantabria +
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Spain +
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23:43:54, 7 November 2019 +
NO STATE +
Hydrology Focus Research Group +
