Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
initiatives is highly desirable. Experience with computational tools (e.g., CFD, FEA, system-level modeling) and/or experimental platforms for energy systems is expected. Position # 2 - Machine Learning and AI
-
designing against diffuse pollution. Typically, these processes are studied by laboratory experiments and/or computational fluid dynamics (CFD) approaches, often limited to an idealised patch of stems where a
-
will be the Head of Department. About the project The successful candidate will be part of the project SAPPHIRE (https://sapphire.norceresearch.no/ ). SAPPHIRE aims to contribute to cleaner and more
-
deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian You will be part of a dynamic research team working on topics relevant
-
changes), Computer Science and Informatics (Numerical Analysis; simulation, optimization and modelling tools; Computational Fluid Dynamics (CFD)), Product and Processes Engineering (Space Engineering
-
Number AE2025-0514 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0514.pdf CALL FOR GRANT
-
modeling and numerical methods Experience with multiphase flow modeling (e.g., TFM, CFD-DEM, DNS, LBM) Solid programming skills Experience working in Linux/HPC environments Ability to conduct independent
-
, applied mathematics, or a closely related field. Strong background in computational modeling and numerical methods Experience with multiphase flow modeling (e.g., TFM, CFD-DEM, DNS, LBM) Solid programming
-
University London was established in 1966 and is a leading multidisciplinary research-intensive technology university delivering economic, social and cultural benefits. For more information please visit: https
-
along with their simulation results (e.g. FEM, CFD) start to “pile up”, rarely being ever used after they have served their purpose. These models can be also seen in the context of product life cycle, i.e