Postdoc: AI-Driven Wind Field Modeling for Coastal Dunes

Utrecht University; Utrecht; On-site; EUR 41,000 - 64,000; Full time

Benefits offered by this job

Holiday pay

Year-end bonus

Pension scheme

Job summary

Universiteit Utrecht is inviting applications for a 2-year postdoc position in coastal dune modelling. You will use numerical modelling and machine learning to increase the accuracy of coastal dune models and to build a surrogate wind field model feeding robust predictions into existing dune simulations.

You will start by evaluating wind field predictions from AeoLiS, train data-driven predictors from CFD data, and apply the new model to case studies.

Qualifications

• PhD in Data Sciences, Computer Sciences, Physics, Earth Sciences, Civil Engineering, or related field.
• Strong data science background with ML experience.
• Experience applying AI techniques to physical systems.
• Strong programming skills (Python preferred).
• Affinity with collecting and analysing field measurements is a plus.

Responsibilities

• Evaluate wind field predictions from coastal dune models against field data or CFD results.
• Train a data-driven wind field predictor using CFD data (e.g., PySR or neural networks).
• Develop a surrogate wind field model and integrate it with the AeoLiS coastal dune model.
• Apply the new model to existing case studies and validate results with stakeholders.

Skills

Data science

Machine learning

Python

Numerical modelling

Field measurements

Education

PhD in Data Sciences

Tools

AeoLiS

CFD

Job description

Universiteit Utrecht is inviting applications for a 2-year postdoc position in coastal dune modelling. You will use numerical modelling and machine learning to increase the accuracy of coastal dune models and to build a surrogate wind field model feeding robust predictions into existing dune simulations.

You will start by evaluating wind field predictions from AeoLiS, train data-driven predictors from CFD data, and apply the new model to case studies.