PhD Position F/M Deep Neural Network-assisted Computational Design of Ultrafast Metasurfaces for Efficient Light Manipulation
il y a 2 jours
We are seeking a highly motivated and talented PhD candidate to join our research team at INRIA, where you will embark on an exciting journey to develop cutting-edge computational design methods for ultrafast metasurfaces. As part of this project, you will leverage the power of deep neural networks to optimize the design of active nanostructures, enabling unprecedented control over light manipulation.
About the ProjectThis PhD project is part of a collaborative effort between INRIA and the CNRS-CRHEA laboratory, focusing on the development of innovative numerical methods for systems of partial differential equations (PDEs) modeling nanoscale light-matter interaction problems. Our goal is to push the boundaries of metasurface research by creating a novel ANN-assisted reduced-order modeling (ROM) strategy, capable of efficiently simulating complex electromagnetic phenomena.
Your RoleAs a PhD candidate, you will be responsible for:
- Bibliography study on existing ANN-based ROM methods
- Formulation of an ANN-based ROM method for time-domain nanophotonics in the context of electrically-driven active metasurfaces
- Development of the method for 3d problems using Fortran 2003 and Python
- Detailed assessment of the novel ANN-based ROM method by considering model problems
- Formulation and development of an inverse design workflow that leverages the novel ANN-based ROM method
- Application of the inverse design methodology to numerical optimization of electrically-driven active metasurfaces
To succeed in this role, you should possess:
- Solid knowledge of numerical analysis for PDEs
- Familiarity with Machine Learning / Deep Learning and Artificial Neural Networks
- Basic understanding of physics of electromagnetic wave propagation
In addition to the opportunity to contribute to groundbreaking research, we offer:
- A gross salary of €2100 per month (year 1 & 2) and €2190 per month (year 3)
- Subsidized meals
- Partial reimbursement of public transport costs
- 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours)
- Possibility of teleworking and flexible organization of working hours
- Professional equipment available
- Access to vocational training
- Contribution to mutual insurance (subject to conditions)
The estimated monthly salary is based on industry standards and takes into account factors such as location, experience, and qualifications.
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