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| Post-doc position in Machine Learning applied to the modelling of 21-cm signal from the Epoch of Reionization | Closing date: 2021-03-01
Contact: Benoit Semelin |
| The MINERVA project, funded by the Paris Observatory Scientific Council, is offering a post-doctoral position to work on applications of machine learning to the interpretation of the 21-cm signal from the Epoch of Reionization as observed by NenuFAR and later on by the SKA. The expected starting date is September 2021. | | ▸ more | Radioastronomy is experiencing an explosion of the volume of observational data with the development of giant interferometers (LOFAR, ALMA, NenuFAR, SKA). At the same time, model predictions, often resulting from HPC numerical simulations, are also producing massive data. In parallel, machine learning methods have undergone algorithmic developments that bring them to a high level of maturity.
The successful candidate is expected to work on applications of machine learning methods to the measurement and interpretation of the 21-cm signal from the Epoch of Reionization. Possible avenues of research are the application of Machine Learning to forward or backward modelling of the signal to provide alternative parameter constraints methods, the enhancement of the modeling itself (numerical simulations) with Machine Learning, exploring the use of Machine Learning to speed up the calibration of observations, the use of unsupervised learning for signal characterization, etc?The candidate is also welcome to suggest his own ideas within this general context.
The successful candidate will have access to computing ressources dedicated to MINERVA (a dedicated GPU computing node).
The LERMA/Observatoire de Paris maintains a lively visitor program and hosts regular workshops and conferences throughout the year. The successful candidate will be immersed in an internationally visible research environment in the Paris Campus. Funding will also be allocated for travel.
Further details are available at:
https://vm-weblerma.obspm.fr/minerva/open-position-3/
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