This research provides for the development and application of machine learning techniques
for the implementation of a precipitation statistical downscaling model at the basin scale. In
this regard will be studied various models, from convolutional neural networks (CNN) to
ensemble techniques and stacking models, with application to the case study of the Apulia
Applicants are Italian and foreign in possession of scientific and professional curriculum
suitable for the conduct of research activities related to the invitation.
Master Degree in Environment and Territory Engineering, Civil Engineering or similar.
Research experience in environmental engineering and hydrological extremes. The activity
has to be documented with ISI/Scopus papers.
Foreign candidates must have adequate knowledge of the Italian language.
Eligible destination country/ies for fellows:
Eligibility of fellows: country/ies of residence:
Eligibility of fellows: nationality/ies:
The interview will tend to evaluate the experience of candidate on the characterization
of hydrological extremes, on the development of models based on machine learning
techniques, on the implementation of Matlab and R routines. The knowledge of Italian
language will be also verified during the colloquium.
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