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Join the Helmholtz Association as a Postdoc focusing on AI-based consulting systems for multiphase CFD simulations. This position offers a platform for innovative research, requiring a strong background in data sciences and programming, to advance the field of computational fluid dynamics through machine learning.
Scientific / postdoctoral posts
01.08.2025
With cutting-edge research in the fields of ENERGY, HEALTH and MATTER, around 1,500 employees from more than 70 nations at Helmholtz-Zentrum Dresden-Rossendorf (HZDR) are committed to mastering the great challenges facing society today.
The Institute of Fluid Dynamics is conducting basic and applied research in the fields of thermo-fluid dynamics and magnetohydrodynamics in order to improve the sustainability, the energy efficiency and the safety of industrial processes.
The Department of Computational Fluid Dynamics is looking for a Postdoc (f/m/d) AI-based consulting system for applied multiphase CFD simulation.
We have developed a comprehensive database of computational fluid dynamics (CFD) simulation cases and are currently creating a performance matrix to evaluate CFD closure models. The over-arching goal is to conserve the experience gained with every CFD simulation. This data-driven approach allows us to apply machine-learning techniques to infer connections between the feature space of our CFD cases, closure models and the performance of their interaction, based on which a recommender system is developed to predict the best model set for new CFD cases.
Your tasks# Identify, implement, test and ensemble suitable recommender algorithms (collaborative/content-based filtering etc.)
# Strategy to collect and store relevant data for the long-term built-up of a performance database (for the interaction between CFD case and CFD closure model)
# Development of a performance metric characterizing the speed of each model
combination (computed from the runtime statistics on our HPC cluster)
# Use multiple matrices (i.e. for accuracy, robustness and speed performance) for different
user needs to allow for a flexible usage of the recommender system application
# Development of a strategy for user feedback with given recommendations (explicit/implicit)
# Completed university studies (Master or PhD) in the field of data sciences or related field
# Strong foundational knowledge about recommender systems and associated algorithms
# Experience with data retrieval and storage to build a sustainable dataset
# Out-of-the-box attitude to newly apply machine-learning methods to a natural science field
# Excellent programming knowledge in Python
# Excellent language skills (written + verbal English)
# A vibrant research community in an open, diverse and international work environment
# Scientific excellence and extensive professional networking opportunities
# Salary and social benefits in accordance with the collective agreement for the public sector (TVöD-Bund) including 30 days of paid holiday leave, company pension scheme (VBL)
# We support a good work-life balance with the possibility of part-time employment, mobile working and flexible working hours
# Numerous company health management offerings
# Employee discounts with well-known providers via the platform Corporate Benefits
# An employer subsidy for the "Deutschland-Ticket Jobticket"
We look forward to receiving your application documents (including cover letter, CV, diplomas/transcripts, etc.), which you can submit via our online-application-system.
This research center is part of the Helmholtz Association of German Research Centers. With more than 42,000 employees and an annual budget of over € 5 billion, the Helmholtz Association is Germany's largest scientific organisation.