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EPFL’s Chair of Numerical Modelling and Simulation in Lausanne seeks a postdoc to lead research on topology optimization for architected materials using fast simulation techniques. You will develop and implement unfitted finite element methods, domain decomposition, reduced order modeling, or isogeometric analysis, and publish results in top journals.
Collaboration with PhD students and contributions to teaching are expected.
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EPFL, the Swiss Federal Institute of Technology in Lausanne, is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs more than 6,500 people supporting the three main missions of the institutions: education, research and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of more than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries.
The Chair of Numerical Modelling and Simulation at EPFL is dedicated to the design and analysis of numerical algorithms for partial differential equations. Our research is oriented towards the development of novel and innovative numerical techniques aiming at improving the integration between numerical simulations and geometric modelling and processing.
Within the project «FLASh: Fast simulation tools for LAttice Structures» , funded by the Swiss National Science Foundation, we are opening a postdoctoral position for developing efficient algorithms for the topology optimization of architected materials using finite element technique
As a postdoc in our group, you will lead research on the design and implementation of mathematically sound methods for the topology optimization of architected materials, leveraging fast simulation techniques such as unfitted finite element methods, domain decomposition, reduced order modeling, or isogeometric analysis. You will work in a dynamic and collaborative environment, contributing to both the theoretical development and the software implementation of these methods. More specifically: