PhD Student in Machine Learning for Integrated Resource Systems Analysis at Kungliga Tekniska Högskolan

Language

Location: Stockholm
Type: Full-time, Other
Level: intern
Posted: Sep 30, 2026

Description

KTH is seeking a PhD student to work on transforming energy systems and integrated resource analysis methods using machine learning. The research will develop workflows for exploring uncertainties and broad scenario spaces in large, detailed models, with applications to developed and developing country contexts. The student will also engage with authorities and stakeholders, participate in capacity development, and collaborate with external partners. The role is supervised by Francesco Gardumi, requires advanced-level education and English B/6, and offers employment benefits and a monthly salary subject to KTH's PhD student salary agreement.

Required Skills

Machine learning
Integrated resource systems
Data processing
Modeling
Capacity development

Additional Information

Minimum Education: Advanced-level degree or equivalent higher education qualifications, including at least 240 higher education credits with at least 60 at an advanced level, or substantially equivalent knowledge.
Required Previous Experiences: Knowledge of energy technology and integrated resource systems
Field modeling, data processing, and machine learning
Stakeholder and external partner collaboration
Preferred Qualifications: Independent work initiative
Collaboration
Professional approach
Complex issue analysis
Translation Company Name: Kungliga Tekniska Högskolan