DC14: Modelling of low-frequency breathing of turbulent separation bubble

PhD Position
Modelling of low-frequency breathing of turbulent separation bubble


MSCA-DN FairCFD, DC14

We are seeking to recruit an outstanding Doctoral (PhD) Candidate to join the new MSCA Doctoral Network “FairCFD”. The doctoral research will be carried out at Technische Universität Berlin (Germany) under the supervision of Prof. Kilian Oberleithner. The position is funded for 36 months and includes secondments with international academic partners in France and Italy. For more details about the network’s philosophy and actions, see the FairCFD website.

Within the FairCFD Doctoral Network, you will benefit from a unique three-fold experience:

  • Contribute to innovation in renewable energy by developing advanced and efficient CFD strategies.
  • Participate in a network-wide interdisciplinary effort to define and promote sustainable numerical practices in scientific computing.
  • Join a vibrant European network of 15 doctoral candidates, with access to high-level training, cutting-edge events, and exposure to both academic and industrial environments.

Scientific background

This PhD project addresses the significant challenge of simulating flows that exhibit very large-scale and very low-frequency turbulent flow dynamics. Despite their relevance for applied aerodynamics, current CFD tools struggle to capture these phenomena. To overcome this, we propose a hybrid approach that combines RANS-based data assimilation and physics-based linear dynamic modeling. The goal is to develop a framework capable of detecting these large-scale structures and uncovering their underlying mechanisms.

We aim to apply this method to study the low-frequency breathing observed in turbulent separation bubbles (TSB), which has substantial technological implications. These dynamics can cause vibration, noise, mechanical fatigue, and fluctuating thermal loads. For instance, in hydraulic turbines [1], unsteady flow separation can lead to reduced efficiency and performance degradation. Similarly, in transonic compressor blades [2], the oscillation of the shock position due to TSB unsteadiness influences the working range, stall onset, and buffeting characteristics.

To tackle this, we propose a novel hybrid approach that integrates experimental data, numerical simulations, and physics-based modeling [3].

Selected references:

  • Duquesne, Y. Maciel and C. Deschênes, “Unsteady flow separation in a turbine diffuser”. (2015) Exp. Fluids, Bd. 56, p. 1–15. https://doi.org/10.1007/s00348-015-2030-7
  • Hergt, J. Klinner, J. Wellner, C. Willert, S. Grund, C. Steinert and M. Beversdorff, “The Present Challenge of Transonic Compressor Blade Design”. (2019) J. Turbomach., Bd. 141, p. 091004. https://doi.org/10.1115/1.4043329
  • Fuchs LM, Steinfurth B, von Saldern JGR, Weiss J, Oberleithner K. Standing-wave dynamics in low-frequency breathing of a turbulent separation bubble. Journal of Fluid Mechanics. 2026;1030:A34. https://doi.org/10.1017/jfm.2026.11191

Your research program

The project aims to develop a hybrid data-assimilation and modelling framework to uncover and predict the large-scale, low-frequency dynamics of turbulent separation bubbles (TSBs), a key source of vibration, noise, and performance degradation in hydraulic turbines and transonic compressor blades. By combining RANS-based data assimilation with physics-based resolvent analysis, the PhD will establish a computationally efficient approach to model the mechanisms driving these unsteady flow phenomena.

Key tasks:

  • 3D data assimilation: Extend advanced assimilation techniques (such as PINNs, Bayesian inference, and adjoint methods) to reconstruct realistic three-dimensional mean fields of TSBs from experiments and RANS simulations.
  • 3D resolvent modeling: Develop a time-stepper-based and quasi-3D resolvent analysis in the FELiCS code to identify the most amplified, low-frequency structures governing TSB dynamics.
  • Low-order model development: Build a reduced-order dynamic model capable of reproducing and explaining the breathing behavior of TSBs across different configurations.
  • Application and validation: Apply the framework to benchmark cases, including the forward-facing ramp, NASA hump, and Boeing hump, in collaboration with experimental partners. Extension to compressible flows and/or shape sensitivity analysis are possible. 

Expected outcomes include a generalizable, efficient framework for capturing low-frequency unsteadiness in separated flows, advancing both the fundamental understanding and industrial modelling of complex aerodynamic systems.

Work environment

For the main part of your work, you will be hosted in Technische Universität Berlin. The Technische Universität Berlin is one of the largest technical universities in Germany, hosting more than 30.000 students, almost 20% being internationals. TUB also has a leading position in terms of gender aspects among German universities. The Institute of Fluid Dynamics and Technical Acoustics (ISTA) within the Department of Mechanical Engineering and Transport Systems performs teaching and research related to experimental and numerical fluid dynamics, acoustics and combustion. It currently employs about 100 members of staff. Besides fundamental research, development work is being performed for major companies in power generation as well as in transportation.

Integration within the FairCFD Network

Within the FairCFD network, you will contribute mainly to WP1: Efficient physics-based numerical methods and WP3: Judicious combination of physics and data.

You will regularly exchange with other DCs of the network applying similar approaches to other problems, and/or applying different numerical methods to similar problems.

Two secondments (short research stays in other partners of the network) are planned during the PhD: with 1/ ONERA (6 months, France): Adjoint-based assimilation and quasi-3D resolvent analysis; 2/ POLIMI (3 months, Italy): Dynamic modelling of transonic flows, focusing on buffeting and fluid-structure interaction.

Interdisciplinary task: co-designing numerical frugality 

Beyond your individual research program described above, you will contribute along with all other FairCFD doctoral candidates to a network-wide multidisciplinary effort (WP5) addressing the environmental and societal dimensions of numerical simulation.
Each DC will participate in the definition of practical metrics for numerical frugality (computational cost, energy use, resource impact) and contribute data from their simulations to a collective meta-analysis. This initiative will be supported by interdisciplinary experts and accompanied by a dedicated DC in social sciences, who will lead a qualitative study on evolving practices in simulation across the network. Together, we aim to make concrete, informed recommendations for sustainable scientific computing.

Network Training Program — More Than Just a PhD

As a Doctoral Network funded by Marie Sklodowska-Curie Actions (MSCA-DN), FairCFD will offer you rich and engaging training experience, including

  • Four one-week training events; (i) an induction week devoted to team-building, open-science practices and sustainability issues, (ii) an Essential Skills Accelerator event combining aiming to equip DCs with essential technical and transferable skills, (iii) a Hackathon event where DCs will collaborate in teams to solve complex physics problem and compare various simulation strategies in terms of precision and sobriety, and (iv) a Career and Leadership Development Forum Aiming to equip DCs with transferable skills essential for their future careers.
  • Five Online courses combining technical training with state-of-the art simulation methods ranging from physics-based approaches to data-driven ones, exposition to industrial applications, along with Social, ethical and environmental aspects of decision-making in modelling practices.
  • Involvement in the organization of scientific events, including a mini-symposium as part of a large-audience scientific conference, a scientific symposium allowing to share the output in terms of new methods, innovation, and applications to industrial processes, and a Societal colloquium to deliver the outputs of the multidisciplinary tasks of the network.

This program is designed to support your growth as a researcher, innovator, and engaged citizen, fully equipped to lead the next generation of responsible simulation science. See our website for more details.

Where to apply

The candidates should send a CV, cover letter, BSc and MSc degrees (certified copies plus translation in English) and two letters of recommendation. Copies of the reference publications can be sent upon request. Personal interviews might be asked.

All applications must be mailed here with subject: “FairCFD, application to DC14”.

This call will remain open until May 31st.

Note that applications within the FairCFD network are limited to 2 DC positions per candidate. If you want to apply to 2 positions please indicate this in your application and indicate your preference. Applications not respecting this rule will be discarded.

Requirements

Research Field

Engineering » Mechanical engineering

Education Level

Master Degree or equivalent

Skills/Qualifications

  • Master’s degree (or equivalent) in fluid mechanics, applied mathematics, scientific computing, or related fields.
  • Strong background in fluid mechanics, numerical methods, PDEs, and/or data-driven modeling.
  • Interest in interdisciplinary research and open science.

Additional Information

Benefits

The successful candidates will receive an attractive gross salary of 7.400€ per month in accordance with the MSCA regulations for Doctoral Researchers. The exact (net) salary will be confirmed upon appointment and is dependent on local tax regulations and on the country correction factor (to allow for the difference in cost of living in different EU Member States). The salary includes a living allowance, a mobility allowance, and a family allowance (if applicable). The guaranteed PhD funding is for 36 months (i.e., EC funding, additional funding is possible, depending on the local Supervisor, and in accordance with the regular PhD time in the country of origin).

Eligibility criteria

According to the international mobility rules of the MSCA-DN program, the candidates must not have spent more than 12 months in the hosting country (Germany), during the 36 months preceding the starting of the PhD. Apart from this rule, worldwide applications are expected and encouraged.

Selection process

The application process is officially opened on April 1st 2026 and will be active up to May 31st . Meanwhile, additional information can be obtained by contacting the supervisors along with the DN coordinating team. For this sake, please contact us by e-mail using this contact link, mentioning “[FairCFD] Application to DC14” in the subject of the e-mail.

Additional comments

A start date will be negotiated with the successful candidate. Ideally start dates would be between August 2026 and September 2026.