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Albert Lau

1 week ago

PhD Candidate in Quantifying the Benefits of Wayside Detection for Railway Infrastructure Norwegian University of Science and Technology in Norway

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Oct 31, 2026

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Country

Norway

University

Norwegian Institute of Science and Technology

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Keywords

Computer Science
Mechanical Engineering
Mathematics
Operations Research
Risk Assessment
Civil Engineering
Industrial Engineering
Causal Inference
Cost Analysis
Asset Management
Statistics
Statistical Modelling
ML

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About this position

NTNU (Norwegian University of Science and Technology) is offering a full-time PhD position in the Department of Civil and Environmental Engineering in Trondheim, Norway. The project focuses on quantifying the benefits of wayside detection for railway infrastructure, with an applied research setting and collaboration with railway-sector partners.

The research is centred on TrainGate, a system that uses trackside inspection portals to monitor passing trains at operating speed. The PhD candidate will combine image, acoustic, vibration, and identification data to detect and track defects in wheels, brakes, pantographs, and other components. A key objective is to link early detections and warnings to maintenance, incident, operational, and cost data, and then develop quantitative methods to estimate impacts on infrastructure degradation, maintenance needs, operational risk, punctuality, and overall costs.

The project aims to produce and validate a practical and transparent benefit-assessment tool for selected TrainGate cases. The tool will compare detection and intervention scenarios and support maintenance decisions, investment assessments, and implementation choices, subject to data availability and partner agreements. The project is funded by the Norwegian Railway Directorate.

The role includes doctoral education, at least 30 ECTS of coursework, data collection and structuring, statistical/causal/machine-learning method development, publication and dissemination of results, participation in research and international activities, and teaching and departmental duties equivalent to one year across the four-year employment period.

Eligible applicants should have a relevant Master's degree in civil, structural, mechanical, railway, or transport engineering, computer science, data science, statistics, mathematical sciences, industrial economics, operations research, or a closely related field. Applicants must have strong academic results, excellent English, and good programming/data-analysis skills. Experience in railway engineering, condition monitoring, infrastructure maintenance, rolling stock, sensor data analysis, statistical modelling, machine learning, life-cycle cost analysis, risk analysis, or operations research is highly relevant.

The appointment is for four years at 100% employment, with a gross salary normally NOK 580,000 per annum depending on qualifications and seniority. The deadline for applications is 31 October 2026. Applications must be submitted electronically through Jobbnorge.no and include the required academic documents, a research plan, and references.

Funding details

Available

What's required

Applicants must meet admission requirements for the Faculty's Doctoral Programme in Engineering. A relevant Master's degree is required in civil engineering, structural engineering, mechanical engineering, railway engineering, transport engineering, computer science, data science, statistics, mathematical sciences, industrial economics, operations research, or another closely related field. Master students may apply, but the degree must be completed and documented before starting. Candidates need a strong academic background, with an average grade equivalent to B or better on NTNU's scale, or a comparable foundation if letter grades are not used; weaker academic records may be offset by exceptional suitability such as relevant work experience and/or peer-reviewed publications. Excellent written and oral English is required, along with good programming and data-analysis skills (e.g., Python, MATLAB, R). Relevant knowledge or experience in railway engineering, infrastructure maintenance, rolling stock, condition monitoring, sensor data analysis, statistical modelling, machine learning, life-cycle cost analysis, risk analysis, or operations research is expected. Preferred qualifications include interdisciplinary engineering/transport and quantitative methods, railway-sector data or maintenance planning experience, publication or reproducible analysis experience, and knowledge of Norwegian or another Scandinavian language.

How to apply

Apply electronically via Jobbnorge.no before the deadline. Include transcripts and diplomas for Bachelor's and Master's degrees, CV, a copy or draft of the Master's thesis, a research plan of no more than 10 pages, relevant academic works if applicable, and contact information for three referees. If you used generative AI in preparing application materials, identify the tool(s) and explain how they were used.

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