PhD Position in Mathematics or Mathematical Statistics with Focus on Geometric Deep Learning

4 days ago


Umeå, Västerbotten, Sweden Umeå University Full time

Project Overview

The project aims to deepen the mathematical theory of geometric deep learning, a subfield of neural network theory that concerns symmetries in data or learning tasks and constructing neural networks that react properly to them.

Key Research Questions

  • Development of new ways of constructing equivariant networks
  • Description of the resulting models mathematically
  • Direct analysis of how symmetries affect the training of neural networks

Qualifications

To be eligible for this position, applicants must have qualifications equivalent to a completed degree at second-cycle level or completed course requirements of at least 240 ECTS credits, including at least 60 ECTS credits at second-cycle level.

Specific Entry Requirements

Applicants must have completed at least 60 ECTS credits within mathematics or mathematical statistics, of which at least 15 ECTS credits shall have been acquired at second-cycle level.

Required Skills

  • Good programming skills (preferably Matlab or Python)
  • Good written and spoken English knowledge
  • Documented knowledge and experience in machine learning, image analysis, probability theory, differential geometry, algebra, optimization, representation theory, and functional analysis

Employment Details

The employment is a full-time paid position, for a fixed term of four years full-time or up to five years when teaching part-time.

Main Tasks

  • Pursue third-cycle studies, including active participation in research and third-cycle courses and activities
  • Participate in the WASP graduate school
  • Teaching or other departmental work (up to 20% of a full-time post)

Salary

Salary is set according to the salary ladder for PhD positions at Umeå University.



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