Job description
Climate change and the race to decarbonize our society is making extreme events in fluids more prevalent. These are rare events where the flow suddenly takes extreme states far from its normal state. Among these, one can cite extreme atmospheric events leading to intense draught, rogue waves capable of capsizing boats, or flashback events in hydrogen-powered clean combustors.

Currently, we cannot accurately predict such extreme events due to the chaotic nature of the underlying turbulent flows and the complex multiscale nonlinear interactions at the origin of such extreme events.

In this project, three PhD candidates are sought to explore and develop cutting-edge scientific machine learning techniques that blends deep learning with physics-based techniques to control such extreme events in turbulent flows. Specifically, three capabilities are targeted:

(i) the identification of precursors and data-driven investigation of the mechanisms of extreme events using a blend of physical simulations and explainable AI techniques;

(ii) the forecasting of the turbulent flow before and throughout the extreme events using physics-constrained data-driven models able to self-correct;

(iii) the control of these flows to prevent extreme events, through a blend of model predictive control and deep learning techniques.

These capabilities will be developed and assessed on a set of flows of increasing complexity, up to an engineering-relevant flow, using high-fidelity simulations for data generation.

The successful candidates will develop this new hybrid scientific machine learning/physic- based framework. The candidates will be part of the European ERC-StG project CONTEXT. They will also be members of the AI Fluids lab and work in collaboration with experienced researchers and other PhD candidates specializing in turbulent flows and artificial intelligence at the Aerodynamics Group of TU Delft.

Requirements
The successful candidate meets the following requirements:

1) MSc degree in applied sciences, computer science, mechanical or aerospace engineering.

2) Strong background in fluid dynamics (e.g. MSc thesis on a fluids-related topic), mathematics, machine learning and/or physics

3) Interest in collaborating with a diverse multinational team

4) Proficiency in the English language, both oral and written

Knowledge and experience in the following fields are highly appreciated:

1) machine learning

2) turbulence

3) numerical methods for fluid dynamics

4) different programming languages

5) high performance and parallel computing     

TU Delft
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Aerospace Engineering
The Faculty of Aerospace Engineering at Delft University of Technology is one of the world’s most highly ranked (and most comprehensive) research, education and innovation communities devoted entirely to aerospace engineering. More than 200 science staff, around 270 PhD candidates and close to 3000 BSc and MSc students apply aerospace engineering disciplines to address the global societal challenges that threaten us today, climate change without doubt being the most important. Our focal subjects: sustainable aerospace, big data and artificial intelligence, bio-inspired engineering and smart instruments and systems. Working at the faculty means working together. With partners in other faculties, knowledge institutes, governments and industry, both aerospace and non-aerospace. Working in field labs and innovation hubs on our university campus and beyond.

Click here to go to the website of the Faculty of Aerospace Engineering.

Conditions of employment
Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2872 per month in the first year to € 3670 in the fourth 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 a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

Additional information
For more information about this vacancy, please contact Dr. Anh Khoa Doan: n.a.k.doan@tudelft.nl.

Application procedure
Are you interested in this vacancy? Please apply no later than 15 January 2025 via the application button and upload the following:

• A motivation letter (1 page max.)
• Detailed CV
• BSc and MSc Transcripts
• An extract of a scientific document you wrote in English (e.g. an article or your MSc thesis)
• Names and contacts information of at least two references (support letters can be attached but are not required)

Screening of the applications will begin immediately, and suitable candidates will be invited for an interview.

Please note:

• A pre-employment screening can be part of the selection procedure.
• Applying for an exemption for specific research and educational areas is an obligatory part of the selection procedure for this vacancy. This exemption must be obtained from the Ministry of Education, Culture and Science (OCW) before an employment contract is agreed upon. Click here for more information.
• You can apply online. We will not process applications sent by email and/or post.
• Please do not contact us for unsolicited services.