Climate AI Nordics

Climate AI Nordics

Nordic network for collaborations around tackling climate change using AI and machine learning.

PhD Student for Sustainable and Resource-Efficient Machine Learning

This PhD project targets sustainable and resource-efficient machine learning with a focus on methods that reduce compute, energy usage, memory demands, and associated carbon emissions while maintaining model quality. Your work will include developing new algorithms for resource-efficient learning, data selection, and hardware-aware optimization.

The position is based at the Division of Statistics and Machine Learning (STIMA) within the Department of Computer and Information Science. The project is a collaboration between STIMA and the Sustainable Artificial Intelligence for Sciences (SAINTS) Lab at the University of Copenhagen, providing access to state-of-the-art computing infrastructure like the Berzelius supercomputer.

Key qualifications and skills:

  • A Master’s degree in machine learning, computer science, mathematics, statistics, or physics.
  • Solid programming skills in Python and knowledge of Git and GNU/Linux systems.
  • A strong background in mathematics and experience implementing new models and algorithms.
  • Strong drive towards fundamental research and the ability to work collaboratively.

Deadline: 2026-04-24

Apply through the official recruitment system

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