Green Energy Lab engages students and early-career researchers directly in research and innovation.
From bachelor projects to PhD supervision, we offer opportunities to learn, experiment and contribute to solutions for the energy transition.
We also support lifelong learning and public engagement, linking research to practice and society.
Student opportunities
Students at bachelor and master level can take part in Green Energy Lab through project work and theses.
Opportunities connect to our laboratories in fluid mechanics, energy storage, advanced materials and virtual modelling, as well as to broader expertise in computational mechanics, structural dynamics, materials science, control systems, sensors and AI-based data analysis.
Projects may address energy production, storage, management or efficiency, and are always linked to applied engineering challenges in the energy transition.
Contact our thesis coordinators to discuss bachelor opportunities.
Contact for bachelor projects
Contact for master projects
Education projects and courses
International projects
Collaborative research-based education for optimized performance of wind farms
Strengthens research-based education in cyber-physical systems for wind farm optimization through collaboration between Norway, the USA, and India.
Partners include HVL, NTNU, SINTEF Digital, OsloMet, IIT Jodhpur, IIT Kharagpur, MNIT Jaipur, and North Carolina A&T State University.
Activities at OsloMet include developing a MOOC on “Optimization of Wind Farms” using VR/AR and AI. Funded by the Research Council of Norway through the INTPART-program (International Partnerships for Excellent Education, Research and Innovation).
Global collaborative research-based education for enhancing performance of wind farms (EduWind)
Builds on INTPART collaboration to strengthen international partnerships in renewable energy education, focusing on cyber-physical systems for wind farms.
Activities at OsloMet include contributing to a lifelong learning course on “Key Operation and Maintenance Strategies for Wind Farms”, integrating immersive technologies and linking research, education, and industry practice.
Funded by the Directorate for Higher Education and Skills through the UTFORSK program.
Courses
- Key operation and maintenance strategies for wind farms - A continuing education course providing key insights into operation and maintenance strategies for wind farms.
- Probabilistic machine learning for predictive maintenance of energy systems (student.oslomet.no) – A PhD-level course providing key insights into the use of probabilistic machine learning for predictive maintenance in energy systems.
