Skip to content
Prespa dark mode logo
  • Research
    • Research Topics
    • Research Highlights
    • Projects
  • For Scientists
    • Publications
    • Software
    • Products
    • Tutorials
  • Communication
    • Outreach
    • Media Coverage
    • Education Activities
  • People
    • External Members
    • Former Members
    • CosmoStat Map
  • Events
    • CosmoStat Calendar
  • Jobs
    • Past Offers
  • Location
Past Offers

Machine-learning methods for the cosmological analysis of weak-gravitational lensing images from the ESA satellite Euclid

January 31, 2024July 16, 2024 Martin Kilbinger
Share this post on:
Position: PhD
Deadline:  10/04/2024
Contact: Martin Kilbinger, Samuel Farrens

Details about this position can be found here.

Share this post on:
Post read time 4 sec read

Author: Martin Kilbinger

View all posts by Martin Kilbinger >

Posts navigation

< Permanent researcher position in cosmology
Kick off TOSCA meeting >

Related Posts

Uncovering the three-dimensional cosmological tidal field
Past Offers
Uncovering the three-dimensional cosmological tidal field
Machine Learning for Radio Interferometric Array Design
Past Offers
Machine Learning for Radio Interferometric Array Design
Field-level inference of weak lensing map statistics in the Ultraviolet Near Infrared Optical Northern Survey (UNIONS)
Past Offers
Field-level inference of weak lensing map statistics in the Ultraviolet Near Infrared Optical Northern Survey (UNIONS)
Designed by Nasio Themes || Powered by WordPress