PhD Candidate in Quantifying Benefits of Wayside Detection for Railway Infrastructure
Develop data-driven methods to assess railway maintenance benefits using wayside detection systems and operational data.
Best for:Best for engineers or data scientists with expertise in railway systems, statistical modelling, or machine learning, seeking a structured PhD opportunity at a leading technical university.
Overview
This PhD position at NTNU focuses on quantifying the operational and economic benefits of wayside detection systems for railway infrastructure. The candidate will work with sensor data, maintenance records, and cost analyses to create decision-support tools for railway operators. The project, funded by the Norwegian Railway Directorate, combines engineering expertise with data science to improve railway reliability, reduce costs, and enhance safety. The role involves both research and teaching duties, with a structured doctoral programme and mentorship support. Applicants should have a strong background in engineering, data analysis, or related fields and demonstrate proficiency in programming and statistical methods.
What you'll do
- Complete a doctoral education, including at least 30 ECTS of coursework, to obtain a PhD degree in Engineering.
- Collect, structure, and assess railway sensor data, operational records, maintenance logs, incident reports, and cost data.
- Develop and validate statistical, causal, and machine-learning models to quantify benefits of wayside detection systems.
- Translate research findings into practical decision-support tools for railway maintenance and operational planning.
- Publish research results in peer-reviewed journals and present findings at international conferences.
- Perform teaching and departmental duties equivalent to one year of work during the four-year contract.
- Collaborate with industry partners to integrate research outcomes into real-world railway operations.
Requirements
Degree required: Master's degree in civil engineering, structural engineering, mechanical engineering, railway engineering, transport engineering, computer science, data science, statistics, mathematical sciences, industrial economics, operations research, or a closely related field. Master students may apply, but the degree must be completed before starting the position.
Degree offered: PhD
Language: English; proficiency must be demonstrated through academic work or standardized tests (e.g., IELTS, TOEFL).
Instruction: English
- Strong academic background in engineering, data science, or related fields with an average grade equivalent to B or higher on NTNU’s grading scale.
- Excellent written and oral English proficiency for academic and professional communication.
- Proficiency in programming and data analysis using Python, MATLAB, R, or equivalent tools.
- Relevant knowledge or experience in railway engineering, infrastructure maintenance, condition monitoring, sensor data analysis, statistical modelling, machine learning, life-cycle cost analysis, risk analysis, or operations research.
- Must meet NTNU’s admission criteria for the Doctoral Programme in Engineering.
- No nationality restrictions, but prior degrees must be documented.
- No age limit, but academic readiness and motivation are key.
- No prior experience cap, but relevant work experience may strengthen the application.
Funding & terms
How to apply
Deadline: 2026-10-31
Applicants must submit a complete application via Jobbnorge.no, including transcripts, CV, a copy of the Master’s thesis, a research plan (max 10 pages), relevant academic works, and contact details for three referees. All documents must be in English. If generative AI was used in the research plan, its use must be disclosed.
- Transcripts and diplomas for Bachelor’s and Master’s degrees
- CV
- Copy of Master’s thesis (or draft if recently submitted)
- Research plan (max 10 pages, including references)
- Relevant academic works (published or unpublished)
- Names and contact information of three referees
- Documentation of the scope and quality of education if studied abroad (e.g., diploma supplement or HK-dir statement)
Contact
NTNU Recruitment Office· PhD Application Inquiries
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