Sort by
Refine Your Search
-
Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have
-
Biology, Physics, Applied Mathematics, Computer Science, Bioengineering, Systems Biology or a related field. Proficiency in modelling using differential equations is required. Candidates must have
-
, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will have experience in one or more of these subject
-
techniques from optimization and control theory, scientific machine learning, and partial differential equations to create a new approach for data-driven analysis of fluid flows. The successful applicant will
-
, image processing, inverse problems, partial differential equations, etc. It is not expected that the candidate should be an expert in all these areas, but should have the enthusiasm and ability to absorb
-
Anemometry (LDA), and Particle Image Velocimetry (PIV). Extend existing in-house wind field models (based on stochastic differential equations such as Langevin or Fokker-Planck types). Integrate novel