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KTH Royal Institute of Technology

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Postdoc in AI-driven road network performance prediction and maintenance KTH Royal Institute of Technology in Sweden

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available

Deadline

Aug 20, 2026

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Country

Sweden

University

KTH Royal Institute of Technology

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Keywords

Computer Science
Data Science
Mechanical Engineering
Information Technology
Civil Engineering
Big Data
Statistics
Statistical Modelling
Machine learning

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About this position

Postdoc opportunity at KTH Royal Institute of Technology in AI-driven road network performance prediction and maintenance.

The Division of Highway and Railway Engineering at KTH’s School of Architecture and Built Environment is seeking a motivated postdoctoral researcher for a project on machine learning for pavement management. The work is carried out in collaboration with the Swedish Transport Administration and road-industry partners.

The project focuses on building data-driven decision support tools for predicting pavement performance and planning maintenance and reinforcement. The postdoc will work with extensive pavement performance datasets, extract and analyze pavement condition and traffic data, integrate climate and environmental datasets, and develop validated predictive models of pavement deterioration using advanced machine learning and statistical methods.

This is a research-focused postdoctoral position with opportunities to strengthen independence and prepare for future academic or industry careers. Teaching at various academic levels may also be included. The role is multidisciplinary, combining pavement engineering, mechanics of pavement materials and structures, and machine learning, with opportunities for high-impact publications and practical tools for the road engineering community.

Eligibility and requirements: a doctoral degree or equivalent foreign degree is required by the time the employment decision is made. Preferred backgrounds include Civil Engineering, Mechanical Engineering, Data Science, Machine Learning, or related fields. Applicants should have programming skills in Python, R, or similar languages. Strong experience in machine learning, statistical modeling, big-data analytics, and infrastructure/transportation data is preferred. Knowledge of pavement engineering and deterioration modeling is a merit, and good English communication skills are required.

Location: Stockholm, Sweden. Duration: up to two years. Application deadline: 2026-08-20.

How to apply: Apply in KTH’s recruitment system and upload a CV, diplomas and grades, and a brief research motivation statement (max two pages). Make sure the application is complete before the deadline.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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