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PhD Position Using Machine Learning and Artificial Intelligence for Structural Health Monitoring

About the position

We have a vacancy for a PhD Candidate at the Department of Structural Engineering.

NTNU is working with the Norwegian Railway Directorate and Bane NOR on challenging engineering projects for our future railway systems. This work considers our critical infrastructure, such as existing railway bridges. Using machine learning and artificial intelligence on data obtained from experimental studies and field measurements, we can improve our understanding of the current state of bridges in service. As such, we seek highly motivated individuals with different theoretical backgrounds for a PhD position.

A major problem in infrastructure today is the many bridges that experience deterioration due to ageing while demands on operational conditions such as traffic loads and intensity increase. The infrastructure owners need to ensure that all bridges have satisfactory standards and meet the requirements provided in the regulatory codes. The current standard for inspection is not robust enough to reliably detect structural damage. Consequently, there is a need for research focusing on developing structural health monitoring (SHM) systems that can detect structural damage in existing bridges, also when experiencing variability in operational and environmental conditions.

In a cooperation between the Structural Dynamics Group at NTNU and the Norwegian Railway Directorate, a full-scale bridge is taken out of service and moved to new on-land foundations - The Hell Bridge Test Arena. The test arena is complete with load excitation equipment, measurement systems and several types of sensors. The bridge serves as a full-scale laboratory for research within SHM and damage detection. It provides means to assess and develop new methodologies by data analysis, focusing on advanced structural analysis, big data technology, machine learning, artificial intelligence, and future novel technologies and algorithms. These techniques will enable us to better predict, evaluate and assess dynamic behaviour and establish local and global structural damage.

The Structural Dynamics Group has had a great development over the last ten years, focusing on dynamic simulations, field measurements, system identification, load modelling, remaining service life estimation, and much more. We work with all structural dynamic problems but have particular experience from critical infrastructures of road and rail.

You will report to the supervising professors.

Duties of the position

  • perform measurements by experimental studies using the test arena and existing bridges in service to obtain data for damage detection and SHM assessment
  • implement novel algorithms for machine learning, artificial intelligence and possibly big data analytics to detect and estimate damage
  • establish statistical models, numerical models and perform finite element model (FEM) analysis, simulations and updating
  • participate in national and international scientific conferences and publish results in academic journals

Required selection criteria

The PhD-position's main objective is to qualify for work in research positions. The qualification requirement is that you have completed a master’s degree or second degree (equivalent to 120 credits) with a strong academic background in Structural Engineering, Mechanical Engineering, Computer Science, Mathematical Sciences, Electrical Engineering or equivalent education with a grade of B or better in terms of NTNU’s grading scale. If you do not have letter grades from previous studies, you must have an equally good academic foundation. If you are unable to meet these criteria you may be considered only if you can document that you are particularly suitable for education leading to a PhD degree.

The appointment is to be made in accordance with the regulations in force concerning State Employees and Civil Servants and national guidelines for appointment as PhD, post doctor and research assistant

  • good written and oral English language skills

Preferred selection criteria

  • experience in experimental research (monitoring)
  • experience in developing numerical and statistical models (defined in the scope of the position)
  • experience in data analysis, big data technology, machine learning, AI, computer science, cloud computing, data classification analysis, clustering or structured learning methods
  • experience with software coding in Python or Matlab
  • Norwegian language skills are appreciate

Personal characteristics

  • motivated and ambitious
  • proficiency to carry out goal-oriented work
  • good cooperation abilities
  • excellent communication skills, both written and ora

We offer

Salary and conditions

PhD candidates are remunerated in code 1017, and are normally remunerated at gross from NOK 482 200 per annum before tax, depending on qualifications and seniority. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.

The period of employment is 3 years.

Appointment to a PhD position requires that you are admitted to the PhD programme in Engineering within three months of employment, and that you participate in an organized PhD programme during the employment period.

The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criteria in the latter law will be prohibited from recruitment to NTNU. After the appointment you must assume that there may be changes in the area of work.

It is a prerequisite you can be present at and accessible to the institution daily.

About the application

The application and supporting documentation to be used as the basis for the assessment must be in English or Norwegian.

Publications and other scientific work must follow the application. Please note that applications are only evaluated based on the information available on the application deadline. You should ensure that your application shows clearly how your skills and experience meet the criteria which are set out above. 

The application must include:

  • CV, certificates and diplomas
  • Academic works - published or unpublished - that you would like to be considered in the assessment
  • Name and address of three referees

Joint works will be considered. If it is difficult to identify your contribution to joint works, you must attach a brief description of your participation.

In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal suitability.

NTNU is committed to following evaluation criteria for research quality according to The San Francisco Declaration on Research Assessment - DORA.

General information

Working at NTNU

A good work environment is characterized by diversity. We encourage qualified candidates to apply, regardless of their gender, functional capacity or cultural background. 

The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the innovation capital of Norway with a population of 200,000. The Norwegian welfare state, including healthcare, schools, kindergartens and overall equality, is probably the best of its kind in the world. Professional subsidized day-care for children is easily available. Furthermore, Trondheim offers great opportunities for education (including international schools) and possibilities to enjoy nature, culture and family life and has low crime rates and clean air quality.

As an employee at NTNU, you must at all times adhere to the changes that the development in the subject entails and the organizational changes that are adopted.

In accordance with The Public Information Act (Offentleglova), your name, age, position and municipality may be made public even if you have requested not to have your name entered on the list of applicants.

If you have any questions about the position, please contact Anders Rønnquist, telephone +47 73594663, email anders.ronnquist@ntnu.no. If you have any questions about the recruitment process, please contact Elin Pedersen Nystuen, e-mail elin.p.nystuen@ntnu.no.

Please submit your application electronically via jobbnorge.no with your CV, diplomas and certificates. Applications submitted elsewhere will not be considered. Diploma Supplement is required to attach for European Master Diplomas outside Norway. Chinese applicants are required to provide confirmation of Master Diploma from China Credentials Verification (CHSI).

If you are invited for interview you must include certified copies of transcripts and reference letters. Please refer to the application number IV-131/21 when applying.

Application deadline: 31.05.2021

NTNU - knowledge for a better world

The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.

Department of Structural Engineering

We teach mechanical engineering, engineering and ICT, and civil and environmental engineering. The Department conducts internationally leading research and participates in several large national research projects. The Department of Structural Engineering is one of eight departments in the Faculty of Engineering

Deadline 31st May 2021
Employer NTNU - Norwegian University of Science and Technology
Municipality Trondheim
Scope Fulltime
Duration Temporary
Place of service Gløshaugen

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