Doctoral training in Electrical Engineering and Computational Science, research in nano-Electronic Design Automation.
The main objective of the training part of Doctoral programme is to train graduate engineers with a strong mathematical background to develop and have them apply their skills to solve real life advanced open problems in their domain of engineering, using the most efficient computational tools and appropriate mathematical models.
By the end of the training, students should be able to: 1. elaborate multi-physic and multi-scale original models at the appropriate level of abstraction starting from a sketchy description, in the language of their domains: electrical or mechanical engineering, physical, chemical or bioengineering; 2. reformulate it as a solvable, well posed mathematical problem; 3. carry out any useful mathematical analysis and optimisations; 4. select or develop appropriate innovative numerical algorithms to discretize and solve the problem; 5. understanding how to write a professional computer program which solves the problem, and 6. interpret and present the results to the scientific community or to an industrial client.
The fellows are trained to successfully communicate with teams of engineers, physicists, computer scientists and/or mathematicians, to solve large-scale, complex and difficult practical problems. The research project is related to the challenges of the European Technological Platform in Nanoelectronics - ENIAC and it aims to the development of adequate mathematical models and numerical schemes, and their implementation in a software demonstrator platform dedicated to the complex problems of nano-Electronic Design Automation (nEDA).
The platform will allow the coupled simulation of semiconductor (DD- drift-diffusion) devices, interconnects, circuits, electromagnetic (EM) fields and thermal (TH) effects in one single conceptual and software framework. It should be noted that thermal and cooling analysis requires CFD (Computational Fluid Dynamic) analysis as well. The nEDA platform will also allow the comparison between results of simulation and measurement, in order to validate the new developed methodology, using suitable benchmarks.
For more info:
- www.lmn.pub.ro
- http://tok.lmn.pub.ro/
- http://www.lmn.pub.ro/~daniel/vacancy
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