Two-Year Postdoc: AI-Driven Wind Flow in Coastal Dunes

Laplace Expert Ltd; Utrecht; Remote; EUR 41,000 - 64,000; Full time

Job summary

Utrecht University, Department of Physical Geography, invites applications for a postdoctoral researcher to develop machine-learning methods for wind-flow prediction in coastal dunes. The two-year project blends numerical modelling with data-driven approaches to improve coastal-dune models.

You will evaluate wind-field predictions against field measurements and CFD simulations, train surrogate models using PySR or neural networks, and validate the combined model on existing case studies.

Qualifications

• Applicants should hold a PhD in data science, computer science, physics, earth sciences, civil engineering or a related field by the start of the position.
• A strong background in data science, numerical modelling and machine learning is required; affinity with CFD, AeoLiS or aeolian field measurements is advantageous.

Responsibilities

• Develop machine-learning methods for wind-flow prediction in coastal dunes.
• Evaluate wind-field predictions against field measurements and CFD simulations.
• Train surrogate wind-field models using PySR or neural networks.
• Validate the combined model on existing case studies.

Skills

Machine learning

Numerical modelling

Python

AeoLiS

Computational fluid dynamics

PySR

Neural networks

Education

PhD in data science / related field

Tools

PySR

AeoLiS

CFD

Job description

Utrecht University, Department of Physical Geography, invites applications for a postdoctoral researcher to develop machine-learning methods for wind-flow prediction in coastal dunes. The two-year project blends numerical modelling with data-driven approaches to improve coastal-dune models.

You will evaluate wind-field predictions against field measurements and CFD simulations, train surrogate models using PySR or neural networks, and validate the combined model on existing case studies.