Internship position F/M Reduced-order modeling with Artificial Neural Networks for nanophotonics
il y a 3 semaines
Nanophotonics is the scientific field that studies the interactions between light and matter at the nanoscale. In this context, sub-wavelength structuring of matter allows these interactions to be shaped for various technological and societal applications. Among the technological applications of nanophotonics are the control of solar energy, improving the sensitivity of digital imagers, and improving the extraction and emission of light in optoelectronic devices.
Numerical modeling is extensively used for understanding the physical phenomena underlying light-matter interactions, as well as for tailoring or harnessing these interactions guided by specific performance objectives. The first objective requires numerically solving the system of time-domain or frequency-domain Maxwell equations coupled to differential equations modeling the behavior of propagation media at optical frequencies, while the second goal is addressed by leveraging a numerical optimization algorithm in the framework of an inverse design workflow.
The Atlantis team is developing the DIOGENeS software suite, dedicated to the numerical study of multiscale problems relevant to nanophotonics and nanoplasmonics. DIOGENeS implements several Discontinuous Galerkin (DG) type methods for which the team has developed a long-term expertise. It also includes an inverse design component, which relies on statistical learning-based global optimization methods for single-objective, multi-objective, and robust optimization.
Internship Objectives and Activities
- Study existing ANN-based ROM methods
- Formulate an ANN-based ROM method for time-domain nanophotonics
- Develop the ANN-based ROM method for 3D problems
- Assess the novel ANN-based ROM method by considering model problems
- Publish research results
Required Skills and Experience
- Master's degree in numerical mathematics or scientific computing
- Knowledge of numerical analysis for PDEs
- Basic knowledge of physics of electromagnetic wave propagation
- Programming skills in Python and Fortran 2003
- Strong communication and teamwork skills
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