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PhD student

Position
PhD student

Employer

IHCantabria- Environmental Hydraulics Institute, Universidad de Cantabria

Please, see the following link
https://mutta.ihcantabria.com/en/

Homepage: https://mutta.ihcantabria.com/en/


Location
Santander, Spain

Sector
Government

Relevant divisions
Hydrological Sciences (HS)
Natural Hazards (NH)

Type
Full time

Level
Entry level

Salary
16,422 EUR/year gross annual salary - 12 payments.

Required education
Master

Application deadline
Open until the position is filled

Posted
6 November 2019

Job description

We are looking for a highly motivated PhD student to join our group in order to develop his/her PhD thesis.

POSITION: PhD Student

THE OCCASION OF COVERAGE: Project: RESEARCH AND DEVELOPMENT OF METHODOLOGIES AND TOOLS FOR IMPROVING REAL-TIME FLOOD FORECASTING CAPABILITIES. VALERIA

ENTITY OF ADMINISTRATIVE DEPENDENCY: Fundación Instituto de Hidráulica Ambiental de Cantabria

GENERAL MISSION: Conception or creation of new theories, knowledge, products and techniques performed on a doctoral thesis.

  • GENERAL TASKS
    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.
    Collaborate in the area of study, under the supervision of the thesis advisor or the project manager, and assessment of a given project
  • SPECIFIC TASKS
    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:
  1. 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
  2. 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.

The research project involves hydrology, statistics and maths
The works is performed in close collaboration with the thesis advisor.
We offer flexible freedom to explore new topics, a good international network and a close interaction with recognized experts.
Scientific collaboration with related pronec1s and publication of scientific results are part of the program_

REMUNERATION: 16,422 EUR/YEAR gross salary (12 payments)

DEADLINE FOR APPLICATION: 1st December, 2019

EXPECTED DATE OF JOINING: 3rd January, 2019

Please, see the following link for further details:
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-10-2019