Postdoc in AI-driven road network performance prediction and maintenance.

KTH Royal Institute of Technology; Stockholms kommun; On-site; SEK 384,066 - 548,666; Full time

Job summary

KTH Royal Institute of Technology is seeking a Postdoc in AI-driven road network performance prediction and maintenance. The role involves developing machine learning tools for pavement management and analyzing pavement and traffic data.

The position emphasizes research with opportunities for academic growth and contribution to impactful publications. Candidates should hold a PhD in a relevant field and possess programming skills in Python or R. Join KTH to innovate towards a sustainable society.

Qualifications

• A doctoral degree or equivalent must be obtained by the employment decision time.
• PhD obtained within the last three years is preferred.
• Experience with infrastructure or transportation data is a merit.

Responsibilities

• Develop machine learning tools for pavement management.
• Analyze pavement condition and traffic data.
• Create data-driven decision support tools.

Skills

Programming skills in Python, R, or similar data science languages

Strong background in machine learning

Statistical modeling

Big-data analytics

Good communicative skills in English

Education

PhD in Civil Engineering, Mechanical Engineering, Data Science, Machine Learning, or closely related field

Job description

Postdoc in AI-driven road network performance prediction and maintenance

KTH Royal Institute of Technology, School of Architecture and Built Environment

The Division of Highway and Railway Engineering is seeking a motivated and collaborative postdoctoral researcher for a project on developing machine learning tools for pavement management. The project is conducted in collaboration with the Swedish Transport Administration and partners from the road industry.

The project aims to create data-driven decision support tools for predicting pavement performance and planning maintenance and reinforcement. It will build on extensive pavement performance datasets and apply advanced machine learning and statistical methods to generate predictions and assess the effectiveness of different maintenance and reinforcement strategies. The postdoc will lead work on extracting and analyzing pavement condition and traffic data, integrating them with climate and environmental datasets, and developing validated predictive models of pavement deterioration.

The position is research-focused, with opportunities to strengthen independence and build qualifications for future academic or industry careers. Teaching at various academic levels may also be included. The work will take place in a multidisciplinary environment combining expertise in pavement engineering, mechanics of pavement materials and structures, and machine learning. The role offers opportunities to contribute to high-impact publications and to practical decision support tools for the road engineering community.

Qualifications

Requirements

• A doctoral degree or an equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made.
• PhD in Civil Engineering, Mechanical Engineering, Data Science, Machine Learning, or a closely related field.
• Programming skills in Python, R, or similar data science languages.

Preferred qualifications

• A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline.
• Strong background in machine learning, statistical modeling, and big-data analytics.
• Experience with infrastructure or transportation data (pavement, traffic, weather, or similar).
• Knowledge of pavement engineering and pavement deterioration modeling is a merit.
• Ability to work both independently and collaboratively in a multidisciplinary setting.
• Good communicative skills in English, both spoken and written, as it is required in the daily work.
• Teaching experience is an advantage.
• Awareness of diversity and equal opportunity issues, with a focus on gender equality.

Great emphasis will be placed on personal skills.

Join us at KTH

KTH shapes the future through education, research and innovation. As a leading international technical university, we play an active role in advancing the transition towards a sustainable society. At KTH, you have the opportunity to grow and develop in a creative and dynamic environment, with good working conditions and attractive benefits. Equality, diversity and equal opportunities are essential to quality and form an integral part of KTH’s core values as a university and public authority.

About the employment

The position offered is for, at the most, two years.

It may be the case that a position at KTH is classified as a security-sensitive role in accordance with the Protective Security Act (2018:585). If this applies to the specific position, a security clearance will be conducted for the applicant in accordance with the same law with the applicant’s consent. In such cases, a prerequisite for employment is that the applicant is approved following the security clearance.

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Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence.