PhD Scholar: AI-Driven Asset Health & Maintenance

Chalmers Tekniska Högskola AB; Göteborgs kommun; On-site; SEK 363,000 - 435,000; Full time

Benefits offered by this job

Employee benefits

Living in Gothenburg

Job summary

Chalmers University of Technology in Gothenburg invites applications for a Doctoral student position focused on AI-powered Asset Health Indices for Smart Maintenance. The project develops health indicators by fusing heterogeneous data to support maintenance decisions and prognostics.

The role includes collaboration with industry and academia, and may involve teaching up to 20% of the time. Start date is May 2026 with a fixed-term appointment of four years.

Qualifications

• Master's degree in relevant field (Mechanical/Production/Industrial Engineering, Automation, Data Science or Computer Science).
• Strong written and verbal English communication skills.
• Interest in maintenance, asset management, data-driven engineering, AI or prognostics/health management.
• Motivated, self-driven, curious and able to work independently while contributing to a collaborative research environment.
• For applicants with a 4-year Bachelor’s degree outside Sweden, a 4-year Bachelor’s degree is accepted.

Responsibilities

• PhD position funded for four years with possibility to teach up to 20%, extending up to five years.
• Contribute to AI-powered Asset Health Index modeling and prognostics for maintenance decisions.
• Collaborate with academia and industry, and publish results from research in lab and real-world pilots.

Skills

English language proficiency

Interest in maintenance and AI

Independent yet collaborative

Education

Master's degree (120 credits) in Mechanical/Production/Industrial Engineering, Automation, Data Science or CS

Job description

Chalmers University of Technology in Gothenburg invites applications for a Doctoral student position focused on AI-powered Asset Health Indices for Smart Maintenance. The project develops health indicators by fusing heterogeneous data to support maintenance decisions and prognostics.

The role includes collaboration with industry and academia, and may involve teaching up to 20% of the time. Start date is May 2026 with a fixed-term appointment of four years.