Postdoc: AI-Driven Wind Flow for Coastal Dune Modelling

Sport Society; Utrecht; Hybrid; EUR 41,000 - 64,000; Full time

Benefits offered by this job

Fixed-term contract

Competitive salary

8% holiday pay

Pension scheme

Flexible working

Growth opportunities

Job summary

Utrecht University invites applications for a 2-year postdoc focused on machine learning for wind flow prediction in coastal dunes. You will build a surrogate wind field model by fusing AeoLiS outputs with CFD data and train ML models in Python to deliver fast, data-driven predictions for coastal dune scenarios.

The project aims to enhance coastal dune models and support decision-making, with results disseminated through stakeholder meetings, conferences, and journals.

Qualifications

• PhD required in a relevant field.
• Solid background in data science and ML.
• Experience with numerical modelling and Python is preferred.

Responsibilities

• Evaluate wind field predictions from AeoLiS vs field/CFD data.
• Train ML models (e.g., PySR or neural networks) on CFD data.
• Develop surrogate wind field model and integrate with AeoLiS.

Skills

Machine learning

Python

Data science

Numerical modelling

Education

PhD in Data Sciences/CS/Physics/Earth Sciences/Civil Engineering or related

Tools

AeoLiS

CFD

PySR

Job description

Utrecht University invites applications for a 2-year postdoc focused on machine learning for wind flow prediction in coastal dunes. You will build a surrogate wind field model by fusing AeoLiS outputs with CFD data and train ML models in Python to deliver fast, data-driven predictions for coastal dune scenarios.

The project aims to enhance coastal dune models and support decision-making, with results disseminated through stakeholder meetings, conferences, and journals.