PhD Candidate in Quantifying the Benefits of Wayside Detection for Railway Infrastructure

About this job

https://www.youtube.com/watch?v=_KHQjc4ndas&t=41s About the position As a PhD Candidate with us, you will help turn early railway fault detection into better maintenance decisions and more reliable operations. You will work in an applied research environment with railway-sector partners. Your immediate leader will be the Head of Department. About the project TrainGate uses trackside inspection portals to monitor passing trains at operating speed. Images, acoustic and vibration signals, and identification data are combined to detect and track defects in wheels, brakes, pantographs and other components. The PhD candidate will link TrainGate detections and early warnings with maintenance, incident, operational and cost data and develop quantitative methods to estimate effects on infrastructure degradation, maintenance needs, operational risk, punctuality and costs. The aim is to develop and validate a practical, transparent benefit-assessment tool for selected TrainGate cases. It will compare detection and intervention scenarios and support maintenance decisions, investment assessments and implementation, subject to available data and partner agreements. The project is funded by the Norwegian Railway Directorate. Duties of the position Complete the doctoral education, including at least 30 ECTS of coursework, and obtain a doctoral degree Collect, structure and assess relevant sensor, operational, maintenance, incident and cost data Develop and validate statistical, causal and/or machine-learning methods and turn the results into useful decision support Publish and communicate results and participate in relevant research and international activities Perform teaching and related departmental duties corresponding to a total of one year during the four-year employment period Be prepared for changes to your work duties after employment. Required selection criteria You must meet the requirements for admission to the faculty's Doctoral Programme in Engineering, see Section 6-1 of the PhD regulations for more information. You must have a relevant 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 another relevant Master's degree in a closely related field Master students can apply, but the master's degree must be obtained and documented before starting the position You must have a strong and relevant academic background from your previous studies and have an average grade from your Master's degree study, or equivalent education, which is equal to B or better compared to NTNU's grading scale. If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you have a weaker academic background, you may be considered if you can document that you are exceptionally suited for a PhD education, for example through relevant work experience and/or peer-reviewed academic works. You must have excellent written and oral English skills You must have good programming and data-analysis skills, for example in Python, MATLAB, R or equivalent You must have relevant knowledge or experience in one or more of the following: railway engineering, infrastructure maintenance, rolling stock, condition monitoring, sensor data analysis, statistical modelling, machine learning, life-cycle cost analysis, risk analysis or operations research The appointment is to be made in accordance with NTNUs guidelines for recruitment positions for general criteria for the position. Preferred selection criteria Education or experience combining engineering or transport with data-driven and quantitative methods Experience with railway-sector data, condition monitoring, maintenance planning, asset management, life-cycle cost or cost-benefit analysis Experience with scientific publication, reproducible analysis, field measurements or experimental research Knowledge of Norwegian or another Scandinavian language Personal characteristics To complete a doctoral degree (PhD), it is important that you are able to: Work independently and in a structured way Collaborate and communicate effectively with academic and industry partners Show curiosity and strong motivation for the subject Assess data and evidence, compare perspectives and draw well-founded conclusions Work constructively under pressure and adapt when plans or conditions change Emphasis will be placed on personal qualities. We offer An exciting job with an important mission in society Developing tasks in

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