Machine Learning with Uncertainty for Complex
il y a 15 heures
Position description
**Category**:
- Mathematics, information, scientific, software
**Contract**:
- Internship
**Job title**:
- Machine Learning with Uncertainty for Complex Physics
**Subject**:
- Exploring uncertainty quantification integrated to Neural Networks for Physical Modelling
**Contract duration (months)**:
- 6
**Job description**:
- The intersection of machine learning and physical modeling has witnessed significant growth in recent years [1]. Simultaneously, Uncertainty Quantification (UQ) has emerged as a powerful tool for modeling uncertainties, enabling probabilistic predictions and quantifying confidence in both experimental and theoretical data. By integrating UQ with neural networks, we can enhance the reliability and interpretability of predictions, particularly in complex physical systems. This integration allows for both improved reliability of the computations and a better understanding of the uncertainties inherent in these predictions.- By the end of the internship, the intern will contribute to the development of more robust and reliable machine learning models for complex physical systems, advancing the state-of-the-art in this field. These results could contribute to fields like materials science where costly computations are replaced by machine learning approximations [4].[2] E. Kawasaki, M. Holzmann and L. Adu-Gyamfi, “Data Subsampling for Bayesian Neural Networks”, Sep. 2024 arXiv:2210.09141
[3] H. Wang, E. Kawasaki, G. Damblin, and G. Daniel, “Multivariate Bayesian Last Layer for Regression: Uncertainty Quantification and Disentanglement,” May 2024, arXiv:2405.01761
[4] S. Watanabe et al., “High-dimensional neural network atomic potentials for examining energy materials: some recent simulations,” J. Phys. Energy, vol. 3, no. 1, p. 012003, Jan. 2021, doi: 10.1088/2515-7655/abc7f3**Applicant Profile**:
Position location
**Site**:
- Saclay
**Job location**:
- France, Ile-de-France, Essonne (91)
**Location**:
- Saclay
General information
**Organisation**:
The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas:
- defence and security,
- nuclear energy (fission and fusion),
- technological research for industry,
- fundamental research in the physical sciences and life sciences.
Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners.
The CEA is established in ten centers spread throughout France
**Reference **:2024-33903
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