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statistical and machine learning techniques for dynamic energy system modelling Develop advanced optimization algorithms for building energy management and control (e.g., MPC, RL) Develop and evaluate digital
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The TUM School of Computation, Information and Technology at the Technical University of Munich (TUM) welcomes applications for a PhD or Postdoc Position (m/f/d, 100%, 2 years+) in Numerical Mathematics
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of reactor systems. Knowledge of heat transfer and fluid dynamics for nuclear system applications and reactor safety analyses. Knowledge of computation methods and numerical solvers for engineering
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focuses on building scalable, accreditation-ready analysis workflows to detect and classify microplastics in complex sample types such as drinking water, plant-based beverages, and biological fluids. As a
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industrial and academic partners. The overall goal of the project is to optimize the design of water eletrolyzers for efficient green energy production. You will be conducting Computational Fluid Dynamic (CFD
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A knowledge of fluid dynamics is recommended. Personal characteristics Working as a Postdoctoral fellow requires that you The successful applicant is a highly competent, motivated and ambitious
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(assessment of membrane processes and water quality analysis) are required. Experience in computational fluid dynamics modelling of water treatment and desalination processes is an advantage. Willingness
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 3 months ago
@orau.org Qualifications The successful applicant should have a PhD in science or engineering discipline with experience in running reacting fluid dynamics simulations. Experience with high fidelity, state
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. The role involves setting up experimental models using Particle Image Velocimetry (PIV) and performing Computational Fluid Dynamics (CFD) simulations to analyze fluid flow and deposition patterns. The data
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approaches and research themes here: www.scilifelab.se/researchers/lisandro-milocco/ This project leverages the rise of data-driven dynamic modeling—from fluid dynamics to ecosystem studies—to uncover