-
/interview Demonstrable experience with optimization in numerical modelling. Essential Application / interview Demonstrable computer programming ability (in particular in Python), and to write code that others
-
matching, optimal transport or cell-cycle modelling. Key Responsibilities These include but are not limited to: Leading an independent research project in scientific machine learning and mechanistic
-
and gradient-based optimization methods in optimization of complex structures are significant. The knowledge of programming languages, numerical methods, material properties including their tribological
-
silico medicine institute, providing a world-class, multidisciplinary ecosystem of over 400 clinical and engineering researchers. This role provides an outstanding opportunity to leverage your numerical
-
previous work to channel flows, both with and without wall roughness. The research will focus on, firstly, optimal synchronisation of minimal unit turbulence (MUT), leveraging the simplified dynamics in MUT
-
: Applications accepted all year round Details Data assimilation combines physical models with experimental or numerical data to produce dynamically consistent flow reconstructions. In turbulence, where full