Climate AI Nordics

Climate AI Nordics

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

PhD in AI-Driven Circular Material Recovery for Energy Applications

Circular economy, AI-driven material recovery, and sustainable energy are rapidly growing research areas. Efficiently reusing composite materials can reduce waste and support the transition to a climate-neutral industry.

The Composite Technology group at RISE focuses on fibre-reinforced composites, polymer systems, and circular material solutions. The group’s work is across the full value chain, from material development and processing to testing, recycling, and industrial implementation. The Composite Technology group have access to advanced laboratories, pilot-scale recycling facilities, and state-of-the-art characterization equipment, and collaborates with industry.

This PhD position is part of the REEDEAM Industrial Graduate School (IGS), a collaboration between Mälardalen University, Örebro University, and Luleå Technical University. REEDEAM IGS combines academic research with industrial applications and focuses on three key areas: CO2-free metallurgy and resilient energy systems, AI and automation in the green transition, and effective circular industry practices.

The project will focus on AI-based predictive modeling to improve the recovery, classification, and reuse of composite fibers, polymers, and graphite. The student will be enrolled at Mälardalen University and primarily based in Öjebyn, near Piteå, Sweden. The role offers interdisciplinary training and collaboration across academia and industry, combining data-driven modeling with practical applications.

The position is fully funded, follows a hybrid work model, and may involve travel for advanced courses, seminars, and conferences

Key qualifications and skills:

  • Strong background in mechanics or composite materials
  • Interest or experience in AI/ML, with eagerness to learn and code
  • Programming skills in Python or C++; experience with PyTorch, TensorFlow, or Scikit-learn is a plus
  • Proficiency in English
  • Analytical, creative, and able to work independently as well as in a team

Deadline: February 27th, 2026

Apply here!

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