Publisher
source

Chalmers University of Technology

Just Landed

Doctoral Student in AI-Powered Asset Health Indices for Smart Maintenance Chalmers University of Technology in Sweden

Degree Level

PhD

Field of study

Computer Science

Funding

The doctoral position is fully funded from the start. It is a fixed-term four-year appointment, extendable to five years if teaching or other duties are undertaken for up to 20% of working time. The starting salary is SEK 35,725 per month, valid from May 1, 2026. The doctoral student is employed by Chalmers and receives employee benefits.

Deadline

Nov 30, 2026

Country flag

Country

Sweden

University

Chalmers University of Technology

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Keywords

Computer Science
Mechanical Engineering
Artificial Intelligence
Industrial Engineering
Reliability Engineering
Maintenance Engineering
Asset Management
Prognostics And Health Management
Decision Support System

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About this position

Chalmers University of Technology in Gothenburg, Sweden, invites applications for a fully funded doctoral student position in AI-powered Asset Health Indices for Smart Maintenance.

The project is based in the Division of Production Systems within the Department of Mechanical Engineering. The doctoral researcher will develop and evaluate artificial intelligence methods that combine heterogeneous condition data, maintenance information, operational data, and expert knowledge into transparent indicators of industrial asset condition and degradation.

Research topics include AI-supported condition assessment, predictive maintenance, prognostics and health management, Remaining Useful Life estimation, model interpretation, risk analysis, maintenance prioritisation, asset management, and lifecycle-oriented decision support for complex technical assets. Models will be tested and validated with researchers and industry partners in laboratory and real-world pilot environments.

Applicants must have a relevant master's degree, or an equivalent four-year bachelor's degree earned outside Sweden, in mechanical, production, industrial engineering, automation, data science, computer science, or a related field. Excellent English communication skills and a strong interest in maintenance, asset management, data-driven engineering, artificial intelligence, or prognostics are required. Experience with Asset Health Indices, machine learning, statistical modelling, optimisation, reliability, condition monitoring, industrial data, programming, or decision-support models is beneficial.

The appointment is fully funded, lasts four years, and may be extended to five years with teaching or other duties of up to 20%. The starting salary is SEK 35,725 per month from May 1, 2026. Physical presence is required throughout the doctoral studies, and a valid residence permit must be available by the study start date.

Applications must be submitted in English through the online vacancy system by November 30, 2026. Upload a CV, personal letter, bachelor's and available master's thesis, and transcripts as PDF files. Questions may be directed to Professor Johan Stahre or Professor Anders Skoogh.

Funding details

The doctoral position is fully funded from the start. It is a fixed-term four-year appointment, extendable to five years if teaching or other duties are undertaken for up to 20% of working time. The starting salary is SEK 35,725 per month, valid from May 1, 2026. The doctoral student is employed by Chalmers and receives employee benefits.

What's required

Applicants must hold a 120-credit master's degree or a 60-credit magister's degree in Mechanical Engineering, Production Engineering, Industrial Engineering, Automation, Data Science, Computer Science, or another relevant field. For education earned outside Sweden, a four-year bachelor's degree is accepted. Strong written and verbal English communication skills are required, along with a strong interest in maintenance, asset management, data-driven engineering, artificial intelligence, or prognostics and health management. Applicants should be highly motivated, self-driven, curious, and able to solve problems independently while contributing effectively to a collaborative research environment. Experience in Asset Health Indices, data analysis, machine learning, statistical modelling, optimisation, maintenance engineering, reliability, condition monitoring, prognostics, asset management, heterogeneous industrial data, programming, decision-support or simulation models, and multidisciplinary academic or industrial collaboration is advantageous. Physical presence throughout the study period is required, and a valid residence permit must be presented by the study start date.

How to apply

Apply online through the application form linked from the vacancy page by November 30, 2026. Submit an English-language CV, personal letter, bachelor's and, if available, master's thesis, and academic transcripts as PDF files; applications sent by email or incomplete applications will not be considered.

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