1 Marie Curie European Industrial Doctorate PhD fellowship for Early Stage Researchers EID Project...

Applications are welcome for an opening of an Early Stage Researcher (ESR) to carry out PhD theses as part of the Marie Slodowska-Curie European Industrial Doctorate (EID) “COMPETE” (COMPutationally empowered Electromagnetic industrial TalEnts), leveraging on a partnership between the Politecnico di Torino (Italy) and Thales DMS France (Defence Mission Systems).

We offer 1 full-time Marie Curie scholarship for a period of 36 months with high perspectives in both academic and industrial areas.

50% of the PhD time will be spent in the Politecnico di Torino and 50% in Thales DMS.

This project is meant to be a highly innovative and multi-sectorial research and training program, which will nurture a new generation of electromagnetic modelers, designers and innovators in the field of the advanced electromagnetics industry. COMPETE will prepare them to the present-challenges of the field by providing a solid theoretical knowledge in Computational Electromagnetics (CEM), together with a competitive and on-the-field training in computationally empowered industrial processes.

Advancement of state of the art of optimization, sensibility, and uncertainty quantification empowered by innovative computational techniques of industrial relevance and interactions with Machine Learning strategies developed within the project.

Objectives: EM sources, large scattering surfaces, small circuitry elements as well as well shapes affect variably the overall final result of an industrial design process and, at the same time are affected by uncertainties and variabilities, It is therefore fundamental to assess on one the one hand the impact of variable material, products, and sub-devices variability on the final figures of merits, this to properly tune the investments in the limitation of such variability. On the other hand the overall results need to be computed within safety thresholds which must be estimated with the highest precision possible by the current modelling and design technology. Although the state of the art in this field has achieved several remarkable results in these areas, the level of complexity of the assessments is limited firstly by forward complexity and secondly by the large dimensionality of the relevant degrees of freedom. This individual project will tackle this challenge by investigating an accelerated procedure to obtain forward points of assessment to be used to compute unequally complex sensitivity figure of merit functions. The same framework will be then extended to obtain multi-parameter transfer functions that will lead to uncertainty quantification paradigms which will run several orders of magnitude faster than those available today. The objectives of this individual project will include 1) Investigate multivariate methods applicable to the computational methods investigated in the network. Develop new approaches for baseline optimization and compression based on multidimensional data structures. 2) Investigate advanced models and variabilities from the relevant degrees of freedom for relevant application scenarios within uncertainty quantification frameworks. 3) Hybridizations other technologies within the ITN-EID network.

Expected Results: 1) An innovative framework for the propagation error in the forward (uncertainties) and backward (sensitivity) directions in several scenarios of industrial interest. 2) An innovative framework to perform the sensitivity analysis for dependent structure 3) Implement these approaches hybridized with the other contributions of the network including advanced optimization and machine learning approaches.