PhD Position in Physics: Explore a unique PhD position in building physics-based multilevel surrogate models utilizing neural networks for electromagnetic wave propagation studies. Join an innovative research project at Inria, a leading digital sciences research institute.
PhD Position in Physics-Informed Neural Networks Research
Designation: PhD Position in Building Physics-Based Multilevel Surrogate Models from Neural Networks
Research Area: Building physics-based surrogate models for electromagnetic wave propagation using neural networks in the frequency domain.
Location: Sophia Antipolis, France (Inria Center, Centre Inria d’Université Côte d’Azur)
Eligibility/Qualification:
- Graduate degree or equivalent in a relevant field
- Valued qualifications: Master’s in applied mathematics or scientific computing
- Sound knowledge of numerical analysis for PDEs and Machine Learning/Deep Learning with Artificial Neural Networks
- Basic understanding of the physics of electromagnetic wave propagation
- Proficiency in Python programming, TensorFlow, and Pytorch
- Good level of spoken and written English
- Strong teamwork skills
Job Description:
- Conduct a bibliographical study on physics-based DNNs for wave propagation models and strategies for designing multilevel and distributed physics-based DNNs
- Perform studies in a two-dimensional case focusing on wave propagation modeled by a Helmholtz-type PDE
- Extend studies to three-dimensional systems of frequency-domain Maxwell equations
- Engage in software development activities
- Evaluate and analyze the proposed NN-based physics-based multilevel surrogate models numerically
- Publish research findings
How to Apply: Click on the following link to apply for this position and submit your application online on the Inria website. Make sure to enter your e-mail address to save your application.
Last Date for Apply: November 30, 2024
Don’t miss this exceptional opportunity to contribute to cutting-edge research in physics-based neural networks at Inria. Apply now and be part of an exciting journey in scientific computing and numerical simulations!
