AI-based prediction
of coastal flooding
PhD research opportunity within SHORECAST combining coastal processes, numerical modelling, observations and artificial intelligence.
Bring your curiosity. Help us understand and anticipate a changing coast.
Discover how to applyApplications follow the official UPC Talent Hub call.
Coastal dynamics,
physics and AI.
We are looking for a motivated candidate interested in coastal processes, data science and numerical modelling to develop a PhD thesis within the SHORECAST project.
The research will investigate how the evolution and rotation of embayed beaches influence coastal flooding, combining numerical modelling, in-situ observations and Machine Learning techniques, including Deep Learning.
Particular attention will be given to the value of observed and predicted shoreline information when detailed topobathymetric data are limited, and to how these uncertainties propagate into coastal flooding predictions.
What you will work on
Coastal systems
Selection and characterisation of pilot beaches along the Spanish Mediterranean, including wave exposure, geomorphology and morphodynamic behaviour.
Data & observations
Processing and analysis of oceanographic data, shoreline observations and topobathymetric information.
Numerical modelling
Configuration, calibration and validation of numerical models such as XBeach, including automated simulations for different storms and morphological states.
Machine Learning
Development and validation of ML/DL models to rapidly predict flooding extent, water depth and coastal-impact indicators.
Uncertainty
Evaluation of model performance, generalisation, sensitivity and uncertainty under different hydrodynamic and morphological conditions.
Early warning
Integration of the developed methodologies into the SHORECAST Coastal Early Warning System and participation in validation campaigns.
Who we are looking for
Master's degree in coastal, civil or environmental engineering, marine sciences, data science, oceanography, physics, applied mathematics or a related field.
Knowledge of data science and Machine Learning, including model training, validation and evaluation.
Background in numerical modelling and understanding of coastal hydrodynamic, sedimentary and morphodynamic processes.
Programming experience, preferably Python and MATLAB, together with GIS tools such as QGIS.
Ability to work both independently and collaboratively and to communicate scientific work in English.
Research at
LIM-UPC
The thesis will be developed at the Laboratori d'Enginyeria Marítima (LIM) of the Universitat Politècnica de Catalunya · BarcelonaTech.
The candidate will work alongside the SHORECAST research team and have access to the project's numerical modelling and observational resources.
The position offers training in coastal-process modelling, programming, artificial intelligence and uncertainty assessment, together with opportunities to participate in field campaigns, scientific publications and conferences.
A curious mind.
A changing coast.
Your next step.
Ready to explore coastal science with us? Start your application journey through UPC Talent Hub.
All applications must follow the official call and be submitted through the UPC electronic site linked from Talent Hub. SHORECAST does not collect applications on this page.
Questions about the research? Get in touchOne clear path. Three simple steps.
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Read the call
Check eligibility, deadlines and the project list on Talent Hub. The call allows an application to one R&D project only.
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Prepare your documents
Follow the official checklist and templates, including the CVA model. Check which supporting documents apply to your situation.
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Submit through UPC
Follow the application link on Talent Hub to the UPC electronic site. Complete and confirm your submission there.
Keep the official call close. Talent Hub and its linked call documents provide the full requirements and any updates throughout the process.