International PhD
programme in NUMERICal Simulation
Numerical simulation and scientific computing will face major challenges in the coming years, such as the development of hardware and software architectures able to deliver very high computing power, the development of specific simulation algorithms that run on HPC computers, the generation of data from “simulation experiments”, data analysis with adequate multi-D visualisation systems, statistical analysis, modelling methods combining different scales and physical models and the management of large and complex data sets (BigData).
CEA has been recognized as an expert in scientific and technological research in this strategic area but ambitions to increase its competitiveness by renewing its research organisation and training capabilities, thus developing its expertise, accelerating development, and internationalizing its position. In this context, the NUMERICS project promote cutting edge research in scientific domains with real prospects yet still poorly developed at CEA by proposing an innovative PhD training that focuses on “numerical simulation and scientific computing” as transversal research activities that will act as leading stake for CEA and further outline the existing PhD programme.
The NUMERICS project rely on internal structures (among which Maison de la Simulation) stimulating base camps for all PhD students (research, training, expertise sharing, mutual exchanges). The proposed project targeting 50 international fellowships all along the programme duration stimulate the development of European research and human resource capacities, knowledge transfer between academic institutions and industrial stakeholders and thus strengthen the competitiveness and innovation of EU industries in this competitive area. Training NUMERICS PhDs to the high standard set out in the programme will ultimately lead to producing a new generation of researchers able to answer the societal challenges covered by CEA.Grant Agreement number: 800945 — NUMERICS — H2020-MSCA-COFUND-2017/H2020-MSCA-COFUND-2017