Job Description:

The “Data-Driven Fluid Dynamics” group (ITLR, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart), led by Prof. Heng Xiao, invites applications for a full-time research position as a Postdoctoral Researcher or Ph.D. Student (100% TV-L E 13).

The "Data-Driven Fluid Dynamics" group operates at the forefront of fluid dynamics, data science, and high-performance computing. Our mission is to develop cutting-edge, data-driven methods to address technically demanding and socially impactful challenges in computational fluid dynamics. We leverage machine learning and data assimilation to enhance understanding and improve predictions of multi-scale physical systems in fluid flows. Examples include aerodynamic turbulent flows, laminar-turbulent transitions, and granular and particle-laden flows. Further details about our research can be found on our website (hengx.org).

We are seeking a motivated postdoctoral researcher or Ph.D. student to contribute to a DFG-funded (German Research Foundation) project focused on developing coupled data-driven turbulence and heat-flux models. This research has potential applications in film cooling for high-pressure turbines. The project is a collaborative effort between Prof. Heng Xiao (University of Stuttgart) and Prof. Solkeun Jee (Gwangju Institute of Science & Technology, South Korea). The position is initially limited to three years, with the possibility of renewal for up to six years, subject to mutual agreement and in accordance with university regulations.

What We Will Offer:

We are a growing, international team working at the intersection of machine learning and fluid dynamics. We have a track record of publishing at top-tier journals both in fluid mechanics and in computational methods, such as Annual Review of Fluid Mechanics, JFM, JCP, and CMAME. Former members of our group have found faculty positions in top universities and institutions in the United States and around the world. We will provide you with a friendly but challenging interdisciplinary research environment and support your academic career.You will have the opportunity to work with other researchers to develop innovative and useful data-driven methods for fluid flows. We work closely with experts from academia and industry and care deeply about the real-world impact of our research.

Eligibility:

Applicants for the position are required to have doctoral degree or equivalent in engineering or a related discipline (e.g., Mathematics, Physics). Due to the nature of the research project, we are specifically looking for applicants with knowledge in machine learning and fluid dynamics. Experience with OpenFOAM and Python programming are advantageous. Excellent communication skills in English and the ability to work in an international team are indispensable for the position. Knowledge of German is a plus but not required.

Location: Universitätsstraße 32, 70569 Stuttgart, Germany.

Application:

Please submit your application in one PDF file including a letter of motivation, a curriculum vitae and scans of all of your original transcripts and diploma certificates from each university degree (or stamped, official translations) until 15.02.2025, by email with the subject “Postdoctoral/Ph.D. Student position in Data-Driven Fluid Dynamics” to seiko.shiraki@itlr.uni-stuttgart.de. We will continue to screen applications until the position is filled.

Contact: Inquiry about the position shall be direct to Prof. Heng Xiao:heng.xiao@simtech.uni-stuttgart.de

At the University of Stuttgart, we actively promote diversity among our employees. We have set ourselves the goal of recruiting more female scientists and employing more people with an international background, as well as people with disabilities. We are therefore particularly pleased to receive applications from such people. Regardless, we welcome any good application.

Women who apply will be given preferential consideration in areas in which they are underrepresented, provided they have the same aptitude, qualifications and professional performance. Severely disabled applicants with equal qualifications will be given priority.

As a certified family-friendly university, we support the compatibility of work and family, and of professional and private life in general, through various flexible modules. We have an employee health management system that has won several awards and offer our employees a wide range of continuing education programs. We are consistently improving our accessibility. Our Welcome Center helps international scientists get started in Stuttgart. We support partners of new professors and managers with a dual-career program.

Information in accordance with Article 13 DS-GVO on the processing of applicant data can be found at https://careers.uni-stuttgart.de/content/privacy-policy/?locale=en_US.

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