Thesis Work, 30 Credits - Ai Surrogates From 3d Cfd For Fast Prediction And Accelerated Process Development
AstraZeneca
Gothenburg, Sweden
Ai models for hydrodynamic metrics
Reduced order models (roms)
3d ai models for field mappings
This thesis offers the opportunity to build AI models that predict key hydrodynamic and mixing metrics at a fraction of the runtime compared to traditional 3D mechanistic simulations
Job Summary
This thesis offers the opportunity to build AI models that predict key hydrodynamic and mixing metrics at a fraction of the runtime compared to traditional 3D mechanistic simulations.
As a Thesis Worker at AstraZeneca, you’ll find an environment that’s full of unique opportunities and exciting challenges.
In this project, you will collect simulation data across various geometries, boundary conditions, and operating ranges to train AI models—including reduced order models (ROMs) and 3D AI models capable of field-to-field mappings.
Matching Summary
This thesis offers the opportunity to build AI models that predict key hydrodynamic and mixing metrics at a fraction of the runtime compared to traditional 3D mechanistic simulations.
Skills & Requirements
Must-have
AI models for hydrodynamic metrics
Reduced order models (ROMs)
3D AI models for field mappings
Cross-validation and uncertainty quantification
End-to-end workflow for surrogate model development