PhD positions in Artificial Intelligence for Fluid Mechanics

PhD positions in Artificial Intelligence for Fluid Mechanics

Published Deadline Location
26 Feb 5 Apr Delft

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Challenge The prediction and the control of complex, transitional and turbulent flows
Change Combining human and machine insights to get to the essence of complex physical flows
Impact Design of more efficient aircrafts and windfarms by improved aerodynamic performance

Job description

TU Delft is a top tier university and is exceedingly active in the field of Artificial Intelligence. The AIFluids lab was recently established to foster the use of AI in the Aerospace Sciences. Designing more efficient aircrafts and wind farms requires a deeper understanding of complex flows. The AIFluids Lab is focused on two major challenges of fluid mechanics: the prediction and the control of complex, transitional and turbulent flows.


New experimental techniques and high-fidelity flow simulations are providing larger and more detailed datasets. Using AI algorithms, the AIFluids Lab will leverage numerical and experimental data to build interpretable models of transition and turbulence. Our objective is to combine human and machine insights to get to the essence of complex physical flows, be it in air, water or other media.


This research will lead to models that can be used to design more efficient aircraft and wind farms, and to the development of a new category of AI algorithms able to autonomously control sensors and actuators to manage complex flows and improve aerodynamic performance.


AIFluids have 4 PhD project vacancies:


(1) Prediction of roughness-induced transition using AI. Your role is to develop a large Direct Numerical Simulation database of transitional flows and use AI algorithms to extract informed and predictive models of the underlying physical processes.


(2) Artificial Neural Networks for unsteady wind turbine loads. You will use experimental and numerical data sets to develop and compare Artificial Neural Network surrogate models for wind-turbine blade unsteady surface pressures and tractions.


(3) AI-based flow control for Transition Delay. You will design and develop a real-time, AI-based active flow control system able to control laminar-turbulent transition. You will also demonstrate this capability on a functional prototype in wind tunnel conditions.


(4) AI for Control of Airfoil Self-Noise Reduction. You will develop a numerical framework for the simulation of aerodynamic noise sources over airfoils and implement AI-based sensing and actuation strategies to mitigate acoustic emissions.


Delft University of Technology (TU Delft)


  • An MSc degree in applied mathematics, engineering or physical sciences.
  • Demonstrated competences in one or more of these categories: AI, computer or data science, numerical or experimental fluid mechanics.
  • Affinity with teaching and guiding students.
  • A background in fluid mechanics.
  • Proficiency in oral and written English.
  • The ability to work in a team, take initiative, and be results-oriented and systematic.

Conditions of employment

Fixed-term contract: 5 jaar.

TU Delft offers DAI-Lab PhD-candidates a 5-year contract (as opposed to the normal 4-years), with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3217 per month in the fifth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.



AIFluids is a Delft Artificial Intelligence Lab. Data, Digitalisation and Artificial Intelligence are becoming increasingly important when dealing with major scientific and societal challenges. DAI labs are co-run by experts in ‘the fundamentals of AI technology’ and experts in ‘AI applications’. As a PhD student, you will work with at least two members of the academic staff and three other PhD candidates. In total, TU Delft will establish 24 DAI Labs, where 48 Tenure Trackers and 96 PhD candidates will have the opportunity to push the boundaries of science using AI. You will be a member of the thriving DAI Lab community that fosters cross-fertilization between talents with different expertise and disciplines.


Each team will be driven by research questions which arise from scientific and societal challenges, and contribute to the development and execution of domain-specific education. You will receive a 5-year contract, one year longer than that of a standard PhD. The extra year accounts for an increased educational load in addition to your normal research tasks, and is to be used for introducing new AI, Data and Digitalisation education related activities within our BSc and MSc programs. All team members have many opportunities for self-development.


The DAI Lab AIFluids is led by Davide Modesti and Anh Khoa Doan. You will work in the deaprtment of Aerodynamics, Wind Energy, Flight Performance and Propulsion (AWEP) of the Faculty of Aerospace Engineering (AE).


The Aerodynamics, Wind Energy, Flight Performance & Propulsion (AWEP) Department contributes to the future of aircraft and wind turbines, with a nucleus in Aerodynamics. The future sustainability of air transport depends greatly on innovations. We need to reduce significantly our energy consumption, our emissions and our dependence on fossil fuels. A good proportion of the innovations we need, are in the fields of aerodynamics, flight performance and propulsion. The relationship between aircraft and wind turbines is reflected in, for example, the fact that aircraft propulsion systems and wind turbines are both rotating wing systems with inverted operations. The turbine design directs towards huge, robust machines for application offshore and in energy-generating kites.


  • PhD
  • Engineering
  • 32—38 hours per week
  • University graduate
  • TUD00877


Delft University of Technology (TU Delft)

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