Publisher
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Peter Krajnik

4 months ago

Postdoc in Machining Systems Chalmers University of Technology in Sweden

Degree Level

Postdoc

Field of study

Machine Learning

Funding

Available

Deadline

Expired

Country flag

Country

Sweden

University

Chalmers University of Technology

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Keywords

Machine Learning
Signal Processing
Mechanical Engineering
Electrical Engineering
Materials Science
Artificial Intelligence
Manufacturing Engineering
Tribology
Data Mining
Digital Twin Technology
Acoustic

About this position

Chalmers University of Technology invites applications for a postdoctoral position in Machining Systems within the Division of Materials and Manufacture, Department of Mechanical Engineering. This role offers the opportunity to contribute to cutting-edge research focused on developing a digital twin prototype for tool-wear monitoring on an IIoT digital platform. The research integrates high-frequency, time-synchronous data acquisition from external sensors (such as force and acoustic emission) with machine-internal signals, leveraging advanced data pipelines and AI/ML algorithms to optimize machining operations.

The Division of Materials and Manufacture conducts research across the full value chain, from materials design and processing to advanced manufacturing and characterisation, with a strong emphasis on metallic systems. The division collaborates closely with industry partners and other academic institutions, including KTH, Volvo Group, and Scania, to develop sustainable materials and manufacturing technologies. The research project is implemented within the Chalmers Centre for Advanced Manufacturing Solutions for Next Generation Powertrain (CX).

The successful candidate will supervise master’s and/or PhD students, participate in teaching at the undergraduate or master’s level, and collaborate with industry and academic partners. The position is a temporary full-time employment for two years, with the possibility of a one-year extension. Chalmers offers a dynamic and inspiring working environment in Gothenburg, Sweden, with comprehensive employee benefits, including generous parental leave, subsidized day care, free schools, and healthcare. Swedish language courses are available for non-native speakers.

Eligibility: Applicants must hold a doctoral degree in Mechanical (Production) or Electrical Engineering or an equivalent foreign degree, completed no later than the employment decision. Strong English communication skills, experience with machining, machine tools, and signal processing are required. Additional merits include recent doctoral graduation (within three years), hands-on experience in machining and tribology, process monitoring, and industry collaboration. Social skills and teaching experience are expected.

Application deadline: 16 June 2026. Applications must be submitted in English via the Chalmers application portal. Incomplete applications and those sent by email will not be considered. For further information, contact Professor Peter Krajnik at [email protected].

Funding details

Available

What's required

Applicants must hold a doctoral degree in Mechanical (Production) or Electrical Engineering or an equivalent foreign degree, to be completed no later than the employment decision. Strong written and verbal communication skills in English are required. Experience with machining, machine tools, and signal processing is mandatory. Candidates should demonstrate social skills and the ability to collaborate. Teaching experience and research potential are expected. It is highly meritorious if the doctoral degree was obtained within the last three years prior to the application deadline. Hands-on experience in machining, tribology of metal cutting, process monitoring, and previous collaborative work with industry partners are advantageous. A valid residence permit is required by the start date.

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Professors

Professor

University Name
Country flag

Sweden

Research Interests

Artificial Intelligence

Production Engineering

Mechanical Engineering

Manufacturing Engineering

Digital Twin Technology