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The Max Planck Institute for Solar System Research (MPS) in Göttingen is one of the world's leading research institutions in the field of solar physics and planetary research with around 300 employees. The interdisciplinary research focus is the investigation of the development, diversity and dynamics of planets, moons, small bodies, the sun and solar-like stars. The MPS develops and operates scientific instruments for current and future space missions (e.g. ESA, NASA), and carries out cosmochemical laboratory investigations of meteorites as well as numerical modeling on state-of-the-art supercomputers.

We invite applications for a

Postdoctoral Position (m/f/d) in machine learning for PDEs and turbulence control

Machine learning techniques have enormous potential for the modeling, prediction, and control of nonlinear systems governed by partial differential equations. This project will focus on developing machine learning methods for PDEs, with a particular emphasis on turbulence modeling and turbulence control.

Your Tasks

• Developing machine learning methods for nonlinear PDEs arising in fluid dynamics and related systems.
• Implementing existing machine learning approaches for reduced-order modeling, closure modeling, and flow prediction.
• Proposing new machine learning methods for turbulence modeling and control.
• Training and testing models using data from direct numerical simulations and experiments.
• Investigating whether machine learning can identify efficient control strategies for turbulent flows.
• Studying the interpretability, generalization, and physical consistency of machine learning models for PDEs.
• Exploring how data-driven methods can accelerate simulations and improve prediction in complex turbulent systems.

Your Qualification

• PhD in fluid dynamics, physics, applied mathematics, computer science, or a related field.
• Experience with machine learning, numerical methods for PDEs, TensorFlow or PyTorch, and Python.
• Experience with turbulence, flow control, scientific computing, or data-driven modeling.
• Experience with GPU computing and supercomputers is desirable.
• Good English skills.

Our Offer

• Comprehensive onboarding, professional development and further training opportunities
• Diverse and varied tasks in an international work
  environment
• Renumeration according to TVöDBund, based on qualifications and experience, annual bonus and additional pension scheme (VBL)
• 30 days of vacation plus 4 additional days off
• Full-time and part-time employment; flexible working time and possibility of mobile work
• Collaboration with local bilingual Montessori child care center
• Good connection by public transport
• Corporate health management

Additional Information

• The position is rated in acccordance to public service act (TVöD-Bund) as EG 13.
• Social security benefits are in accordance with the regulations of the civil services.
• The full-time position is available from June 1, 2026 or as soon as possible thereafter.
• Initially the position is available for a period of one year, with the possibility of an extension for one or additional years.
• The application deadline is April 30, 2026.

We look forward to receiving your informative application documents (cover letter, CV, a publication list, a statement of research interests (max. 2 pages) and the names and contact details of two potential referees). Please submit these via the digital application portal (https://www.mps.mpg.de/career/jobs). If you have any questions, please do not hesitate to contact Xiaojue Zhu (zhux@mps.mpg.de). For further information about the group, please visit: https://sites.google.com/view/xiaojue-zhu/home.

The Max Planck Society endeavours to achieve gender equality and diversity. Furthermore, the Max Planck Society seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply. The Max Planck Society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals.