Postdoc (f/m/d) AI-based consulting system for applied multiphase CFD simulations

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)

Your profile

• 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)

Our offer

• 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.

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