Master Thesis: Predictive Maintenance and Degradation Prognostics

Location: Finspång, Sweden. The thesis is conducted in cooperation with experts based in Finspång, Sweden, and Mülheim an der Ruhr, Germany. The position may offer a flexible workplace.

Company

hirify.global develops energy technology and provides low-emission power generation, service, modernization, and digitalization solutions for gas turbines, steam turbines, and generators in more than 90 countries.

What you will do

• Research the state of the art in monitoring, diagnosis, degradation prediction, and prognostics across asset classes and industries.
• Compare heuristic, analytical, physics-based, statistical, and AI-enabled predictive maintenance approaches.
• Develop case studies covering data acquisition, data processing, anomaly and fault detection, degradation prognostics, and maintenance decisions.
• Create a taxonomy comparing maturity, applicability, data requirements, benefits, limitations, and technology drivers.
• Build a selection framework explaining when different predictive maintenance strategies are most suitable.
• Present actionable findings to hirify.global experts and academic stakeholders.

Requirements

• Eligibility to complete a 30 ECTS master’s thesis during spring 2027.
• Enrollment in a relevant engineering master’s program, such as energy engineering, electrical engineering, mechanical engineering, industrial engineering and management, or an equivalent field.
• Broad interest in engineering systems, maintenance, reliability, data analysis, or related disciplines.
• Ability to conduct structured research and critically compare academic methods with industrial applications.
• Confident written and spoken English for collaboration with an international team.
• Ability to work independently and collaborate effectively in a remote environment.

Nice to have

• Knowledge of predictive maintenance, condition monitoring, statistics, modeling, or AI.

Culture & Benefits

• The thesis is intended for two students and combines academic research with industrial guidance.
• Collaboration with experts in monitoring, data processing, and ageing prognosis for materials, components, and machines.
• Employment benefits include reduced working hours, advance vacation, and wellness allowances.
• Potential options for a flexible workplace.
• Work in an international, diverse organization focused on sustainable, reliable, and affordable energy.

Hiring process

• Apply through hirify.global Careers using job ID 304454.
• Ongoing selection applies, and the position may be filled before the application deadline.
• Application deadline: October 2, 2026.