Publisher
source

Chalmers University of Technology

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Postdoctoral Position in Geometry-Aware Predictive Maintenance and Remaining Quality Life Chalmers University of Technology in Sweden

Degree Level

Postdoc

Field of study

Computer Science

Funding

This is a full-time, temporary two-year postdoctoral employment with the possibility of a one-year extension. The position is funded by Chalmers’ Area of Advance Production. The postdoctoral researcher is employed by Chalmers and receives employee benefits; no salary amount is specified. Teaching activities may comprise up to 20%.

Deadline

Dec 6, 2026

Country flag

Country

Sweden

University

Chalmers University of Technology

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Keywords

Computer Science
Mechanical Engineering
Mathematics
Product Development
Industrial Engineering
Digital Twin Technology
Data-driven Modeling

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About this position

Chalmers University of Technology in Gothenburg, Sweden, invites applications for a two-year full-time postdoctoral position in geometry-aware predictive maintenance within the Division of Product Development, Department of Mechanical Engineering.

The project, “Geometry-aware predictive maintenance: linking degradation to product requirements and formalizing Remaining Quality Life (RQL),” develops methods that predict when degradation in tools, fixtures, and machines will make product non-conformance unacceptable. Unlike equipment-focused Remaining Useful Life, RQL connects degradation to product quality, part and assembly variation, and product-level risk.

The researcher will combine simulation, process and condition monitoring, measured geometry, variation simulation, multimodal diagnosis, maintenance decision-making, and data-driven or hybrid physics-based modelling in a machining-to-assembly demonstrator. Relevant interests include mechanical engineering, industrial engineering, predictive maintenance, geometry assurance, digital twins, sensor fusion, AI, machine learning, and product development.

Applicants need a PhD or equivalent in mechanical or production engineering, automation, applied mathematics, computer science, data science, or a related field, plus relevant experience in modelling, simulation, data analysis, or experimental methods. Strong analytical, collaborative, and English communication skills are required. Experience in geometry assurance, tolerancing, condition monitoring, machining, digital twins, inverse problems, industrial collaboration, or experimental validation is advantageous.

The position is funded by Chalmers’ Area of Advance Production and includes employee benefits. There may be a one-year extension, and teaching or supervision activities may account for up to 20%. Physical presence is required. Applications, written in English and submitted as PDFs through the vacancy application form, must include a CV with publications and teaching experience and a personal letter describing previous research, outcomes, and future goals. Deadline: 6 December 2026.

Funding details

This is a full-time, temporary two-year postdoctoral employment with the possibility of a one-year extension. The position is funded by Chalmers’ Area of Advance Production. The postdoctoral researcher is employed by Chalmers and receives employee benefits; no salary amount is specified. Teaching activities may comprise up to 20%.

What's required

Applicants must hold a doctoral degree or equivalent foreign degree in mechanical or production engineering, or a related field such as automation, applied mathematics, computer science, or data science, by the time the employment decision is made. Required experience includes modelling, simulation, data analysis, or experimental methods relevant to the project, together with the ability to independently develop and evaluate research methods. Strong analytical and collaborative skills and proficiency in spoken and written English are mandatory. Meritorious experience includes geometry assurance, tolerancing, variation simulation, robust design, condition monitoring, predictive maintenance, machining, process monitoring, digital twins, inverse problems, sensor fusion, data-driven or hybrid physics-based modelling, AI or machine learning, industrial collaboration, experimental validation, and engineering decision support. A doctorate obtained within the three years before the application deadline is advantageous. Applicants must be able to work physically on site throughout the employment and present a valid residence permit by the start date.

How to apply

Apply through the application form linked from the vacancy page by 6 December 2026. Submit English-language PDF files containing a comprehensive CV with publications and teaching experience, plus a personal letter covering your background, previous research and outcomes, and future goals and research focus. Applications sent by email or incomplete applications will not be considered.

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