PhD Fellow in Distributed Acoustic Sensing for Arctic Railway Infrastructure Monitoring

UiT Norges arktiske universitet; Narvik; On-site; NOK 580,000 - 620,000; Full time

Job summary

UiT Norges arktiske universitet seeks a PhD Fellow in distributed fibre-optic sensing for railway infrastructure monitoring along the Ofoten Line. The project focuses on DAS-based monitoring to enable real-time warnings and predictive maintenance in Arctic conditions.

The successful candidate will develop and validate methods, perform data analysis, and collaborate across departments. The position is four years, with teaching duties in the fourth year, based in Narvik.

Qualifications

• Master’s degree or equivalent in a relevant field; applications welcome near completion.
• Strong English; international environment.
• Experience in data analysis and implementing data analysis tools in a programming language.
• Advantageous knowledge in one or more of the following topics: signal processing, physical/geophysical modelling, computer science, geohazards, waves and fields, material science.

Responsibilities

• Develop, test, modelling and validate DAS-based monitoring methods for railway infrastructure and surrounding terrain.
• Perform data analysis on large-scale datasets from fibre-optic sensing.
• Contribute to algorithm development and potential field work.
• Collaborate with supervisors and other departments to advance research aims.

Skills

Data analysis

Programming in suitable language

Signal processing

Geophysics

Geohazards

Waves and fields

Material science

Education

Master's degree in a relevant field

Job description

The position

A PhD position is available at the Department of Electrical Engineering (IET), Faculty of Engineering Sciences and Technology, UiT The Arctic University of Norway. The position is within the field of distributed fibre-optic sensing for railway infrastructure monitoring, with particular emphasis on the use of Distributed Acoustic Sensing (DAS) for monitoring railway infrastructure and natural hazards along the Ofoten Line.

The position is for a period of four years. The nominal length of the PhD programme is three years. The fourth year is distributed as 25 % each year and will consist of teaching and other duties. The objective of the position is to complete research training to the level of a doctoral degree. Admission to the PhD programme is a prerequisite for employment, and the programme period starts on commencement of the position.

The workplace is at UiT in Narvik. You must be able to start in the position within a reasonable time after receiving the offer.

The position’s field of research

The position is associated with a new research initiative at UiT on intelligent monitoring and resilience of railway and transport infrastructure in Arctic environments that aims to address how distributed sensing, fibre-optic monitoring, environmental observations, drone- and satellite-based data, operational infrastructure datasets, and/or machine learning can be used to support real-time monitoring, predictive maintenance, geohazard detection, and safer railway operations.

The initiative is a collaboration between the Department of Electrical Engineering, the Department of Computer Science and Computational Engineering, and the Department of Geosciences.

Research infrastructure is provided via existing data, sensor networks, and established field sites along the Ofoten Line and new initiatives associated with the Arctic Test Arena project.

Railway infrastructure in Arctic and Nordic regions is increasingly exposed to harsh weather, heavy traffic loads, climate-related hazards, and growing operational demands. Current railway monitoring systems still rely largely on manual inspections and periodic measurements. This makes it challenging to detect early signs of infrastructure degradation, vibration-related damage, geohazards, snow avalanches, rockfalls, landslides, track irregularities, wheel defects, bearing faults, and people and animals on the track.

The PhD project will investigate how existing fibre-optic cable infrastructure along the Ofoten line railway, one of Norway’s most strategically important and climate-exposed railways, can be used as a distributed sensor network for continuous infrastructure monitoring. Standard optical fibres will be used as dense arrays of vibration sensors, making it possible to measure dynamic strain and acoustic disturbances along many kilometres of fibre with down to metre-scale spatial resolution – a technique coined Distributed Acoustic Sensing (DAS). The long‑term ambition is to enable high‑resolution, real‑time warning and decision support for railway operations and maintenance.

The successful candidate will work on developing, testing, modelling, and validating methods for DAS‑based monitoring of railway infrastructure and surrounding terrain.

The work can include physics‑based modelling of e.g., various events and wave propagation through different media, signal processing, large‑scale data analysis, algorithm development and potentially also field work.

The applicants must present a description outlining the academic basis of the PhD project. The project description shall not exceed 2 pages, including reference lists/figures/tables if relevant. It must include a description of the topic, research question(s) and a reasoning of the choices. It should also indicate the methodologies to be used. The final project description will be developed in cooperation with the supervisor.

Qualifications

This position requires a master’s degree or equivalent in applied mathematics, signal processing, physics, geophysics, civil engineering (electrical, geotechnical, structural, environmental, transportation, construction, computer etc.), data/computer science or similar. If you are near completion of your master’s degree, you may still apply.

Applicants must document good English skills and be able to work in an international environment. Nordic applicants can document their English capabilities by attaching their high school diploma.

The Candidate Should Have Expertise In Data Analysis And Be Able To Implement Data Analysis Tools In a Suitable Programming Language. It Is Also Advantageous With Knowledge And/or Capabilities In One Or More Of The Following Topics

• Signal processing


• Physical/geophysical modelling


• Computer science


• Geohazards


• Waves and fields


• Material science

In the assessment, the emphasis is on the applicant's potential to complete a research education based on the master's thesis or equivalent, and any other scientific work. Evaluation of the candidate is not only based on the candidates track record in education, but other experiences that can be relevant for the PhD work. This includes teaching, practical experience with e.g., railway infrastructure and/or other relevant work or activities. The project description will also be considered. In addition, professional experience and other experience of significance for the completion of the doctoral programme will be taken into consideration.

We will also emphasize motivation and personal suitability for the position. We are looking for candidates who:

• Have good communication and interaction with colleagues and students


• Can contribute to a positive and productive working environment


• Are able to work both independently and in groups on defined research topics


• Have good work ethics

As many people as possible should have the opportunity to undertake organized research training. If you already hold a PhD or have equivalent competence, we will not appoint you to this position.

Admission to the PhD programme

For employment in the PhD position, you must be qualified for admission to the PhD programme at the Faculty of Engineering Science and Technology and participate in organized doctoral studies within the employment period.

Admission Normally Requires

• A bachelor's degree of 180 ECTS and a master's degree of 120 ECTS, or an integrated master's degree of 300 ECTS.


• A master's thesis with a scope corresponding to at least 30 ECTS for a master's degree of 120 ECTS.


• A master's thesis with a scope corresponding to at least 20 ECTS for an integrated master's degree of 300 ECTS.

In order to gain admission to the programme, applicants with a background from a Norwegian institution should have a minimum grade of C on their master thesis and a weighted grade average of 3.0 for the last two years of their master programme. A more detailed description of admission requirements can be found here.

If you are employed in the position, you will be provisionally admitted to the PhD programme. Application for final admission must be submitted no later than two months after taking up the position.

Applicants with a foreign education will be subjected to an evaluation of whether the educational background is equal to Norwegian higher education, following national guidelines from Norwegian Directorate for Higher Education and Skills. Depending on which country the education is from, one or two additional years of university education may be required to fulfil admission requirements, e.g. a 4-year bachelor's degree and a 2-year master's degree. UiT normally accepts higher education from countries that are part of the Lisbon Recognition Convention.

Inclusion and diversity

UiT The Arctic University of Norway is working actively to promote equality, gender balance and diversity among employees and students, and to create an inclusive and safe working environment. We believe that inclusion and diversity are a strength, and we want employees with different competencies, professional experience, life experience and perspectives.

If you have a disability, a gap in your CV or immigrant background, we encourage you to tick the box for this in your application. If there are qualified applicants, we invite at least one in each group for an interview. If you get the job, we will adapt the working conditions if you need it. Apart from selecting the right candidates, we will only use the information for anonymous statistics.

We offer

• A dynamic and expanding research environment


• Good career opportunities


• A supportive academic community with committed colleagues


• Flexible working hours and a state collective pay agreement


• Pension scheme through the state pension fund


• PhD Fellows are normally given a salary of 580 000 NOK/year with a 3% yearly increase

Norwegian health policy aims to ensure that everyone, irrespective of their personal finances and where they live, has access to good health and care services of equal standard. As an employee you will become member of the National Insurance Scheme which also include health care services.

More practical information about working and living in Norway can be found here: https://uit.no/staffmobility

Generalinformation

The appointment is made in accordance with State regulations and guidelines at UiT. At our website, you will find more information for applicants.

The engagement is to be made in accordance with 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. After the appointment you must assume that there may be changes in the area of work.

Remuneration for the position of PhD Fellow is in accordance with the State salary scale code 1017. A compulsory contribution of 2 % to the Norwegian Public Service Pension Fund will be deducted. You will become a member of the Norwegian Public Service Pension Fund, which gives you many benefits in addition to a lifelong pension: You may be entitled to financial support if you become ill or disabled, your family may be entitled to financial support when you die, you become insured against occupational injury or occupational disease, and you can get good terms on a mortgage. Read more about your employee benefits at: spk.no.

A shorter period of appointment may be decided when the PhD Fellow has already completed parts of their research training programme or when the appointment is based on a previous qualifying position PhD Fellow, research assistant, or the like in such a way that the total time used for research training amounts to three years.

We process personal data given in an application or CV in accordance with the Personal Data Act (Offentleglova). According tothe Personal Data Act information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure. You will receive advance notification in the event of such publication, if you have requested non-disclosure.