Postdoc: Machine learning for wind flow prediction in coastal dunes

Your job

In this 2-year postdoc position, you will use numerical modelling and machine learning techniques to increase the accuracy of coastal dune models. As a result, your project will inform and enhance decision-making in coastal dune management.

The ultimate goal of this project is to build a surrogate wind field model that can feed accurate wind field predictions into numerical coastal dune models. You will start by evaluating current wind field predictions from the coastal dune model AeoLiS by comparing model output with existing field measurements and/or Computational Fluid Dynamics (CFD) simulations. Specifically, you will assess where simplified assumptions in the model fall short. You will then train a machine learning model (such as PySR or neural networks) on CFD data to develop a fast, data-driven wind field predictor. You will combine this surrogate model with AeoLiS and evaluate the accuracy of the new model setup by applying it to existing case studies. Where needed, you will contribute to field data collection to support model validation. You will share your results in stakeholder meetings, scientific conferences, and academic journals.

Requirements

You have a strong background in data science and experience applying machine learning and other AI techniques. You are interested in applying these techniques to physical systems, in this case, to coastal dunes, wind flow dynamics and wind-driven sand transport.

You have an open, collaborative and curious attitude. You enjoy exploring new approaches and you combine this with the pragmatism that is needed to move a project forward.

By the time the position starts, you have obtained a PhD degree in Data Sciences, Computer Sciences, Physics, Earth Sciences, Civil Engineering, or a related field.

You have a strong background in numerical modelling and programming (preferably Python). You will collaborate with colleagues who are AeoLiS and CFD specialists, so affinity with these techniques is a plus but not required.

Affinity with the collection and analysis of (aeolian) field measurements is a plus.

You communicate clearly and have a strong command of the English language.

Conditions of employment

We offer:

• a position (1.0 FTE) for 24 months.
• a working week of 36 - 40 hours and a gross monthly salary between €3.706 and €5.760 (salary scale 10 under the Collective Labour Agreement for Dutch Universities (CAO NU)). The salary is based on a 38-hour working week;
• 8% holiday pay and 8.3% year-end bonus;
• a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU.

In addition to the terms of employment set out in our collective labour agreement, we offer attractive additional benefits, including opportunities for personal and professional growth, flexible leave arrangements, and extra vacation days. Through the UU Terms of Employment Options Model, you can tailor your employment package to your needs. In this way, we encourage you to grow in what you do, both in your work and in your development. Read more about our terms of employment.

Employer

Universiteit Utrecht

A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University, the various disciplines collaborate intensively towards major strategic themes. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Pathways to Sustainability. Sharing science, shaping tomorrow.

Utrecht University’s Faculty of Geosciences studies the Earth: from the Earth’s core to its surface, including man’s spatial and material utilisation of the Earth – always with a focus on sustainability and innovation. With 3,400 students (BSc and MSc) and 720 staff, the faculty is a strong and challenging organisation. The Faculty of Geosciences is organised in four Departments: Earth Sciences, Human Geography & Spatial Planning, Physical Geography, and Sustainable Development.

Additional information

For more information about this position, please contact Dr Christa van IJzendoorn at c.o.vanijzendoorn@uu.nl. Please do not send your application to this email address but use the ‘Apply Now’ button. Candidates for this vacancy will be recruited by Utrecht University.

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