Pourvu:
Non
Machine Learning techniques have revolutionized artificial intelligence. Their application to astrophysics and cosmology permits us to analyze the large quantity of data obtained with current surveys and expected from future surveys with the aim of improving our understanding of the cosmological model.
Our goal is to apply machine learning techniques to optimally detect and extract photometric redshifts of galaxies detected in large-scale surveys. We have installed a very efficient CNN from Pasquet et al. (https://ui.adsabs.harvard.edu/abs/2019A%26A...621A..26P/abstract) in the pipeline that will be used for the analysis if the aVera Rubin Observatory (https://www.lsst.org/about) LLST (Legacy Survey of Space and Time). The intern will optimize and test this network on simulations, to quantify its performance on single and blended galaxies in the field and in galaxy clusters.
This internship will be hosted by the Cosmology group at the Astroparticle and Cosmology (APC) laboratory, in Paris, and can at a M1 or M2 level. Engineer school (Supelec, Mines, Supaereo, etc.) interns who are looking for long term internships ("cesure", > 3 months starting from September 2024 to November 2024), and M2 students interested to apply for a PhD thesis grant will have the priority. Do not hesitate to contact me if you are interested in this internship and/or a PhD thesis. Please do not forget to send me your grades from the first year of the University to your last year of master.
The internship is funded and available for 3 or 6 months in the period starting from September 2024 to July 2025. The internship will be in collaboration with colleagues at Stanford University, and if the intern is interested, we can fund a period of visit in Stanford. Students who can stay at least 5 months will have the priority.
Our goal is to apply machine learning techniques to optimally detect and extract photometric redshifts of galaxies detected in large-scale surveys. We have installed a very efficient CNN from Pasquet et al. (https://ui.adsabs.harvard.edu/abs/2019A%26A...621A..26P/abstract) in the pipeline that will be used for the analysis if the aVera Rubin Observatory (https://www.lsst.org/about) LLST (Legacy Survey of Space and Time). The intern will optimize and test this network on simulations, to quantify its performance on single and blended galaxies in the field and in galaxy clusters.
This internship will be hosted by the Cosmology group at the Astroparticle and Cosmology (APC) laboratory, in Paris, and can at a M1 or M2 level. Engineer school (Supelec, Mines, Supaereo, etc.) interns who are looking for long term internships ("cesure", > 3 months starting from September 2024 to November 2024), and M2 students interested to apply for a PhD thesis grant will have the priority. Do not hesitate to contact me if you are interested in this internship and/or a PhD thesis. Please do not forget to send me your grades from the first year of the University to your last year of master.
The internship is funded and available for 3 or 6 months in the period starting from September 2024 to July 2025. The internship will be in collaboration with colleagues at Stanford University, and if the intern is interested, we can fund a period of visit in Stanford. Students who can stay at least 5 months will have the priority.
Responsable:
Simona Mei
Services/Groupes:
Année:
2024
Formations:
Stage
Niveau demandé:
M2