PhD Fellow in Multi-Hazard Early Warning System for Critical Underwater Infrastructure Protection

The position

A PhD position is available at the Department of Technology and Safety (ITS), Faculty of Science and Technology with the research group Advanced Maritime Ship Operations.

ITS is organised under the Faculty of Science and Technology and is located at four campuses: Tromsø, Bardufoss, Harstad and Kirkenes. The department has approximately 90 employees and approximately 700 students. It offers undergraduate, master’s, and PhD degree programmes as well as research in the areas of nautical science, aviation, societal safety, environment, and international preparedness.

The position is for a period of three years. 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 Tromsø. You must be able to start in the position in Tromsø within a reasonable time after receiving the offer.

The position’s field of research

Critical underwater infrastructure monitoring will be an important component in securing higher social security and resilience, not only in Norway but also in Europe. The Advanced Maritime Ship Operations research group is dedicated to developing and showcasing a Multi-Hazard Early Warning System for real-time monitoring and protection of critical underwater infrastructure for the same purpose. The position is funded by the INSURE research project funded by the Research Council of Norway, where UiT is the project coordinator. 

The INSURE project aims to develop an AI-powered Multi-Hazard Early Warning System (MHEWS) for real-time monitoring and protection of critical underwater infrastructure, including power cables, communication networks, and pipelines. By integrating fiber optic sensing (OptoDAS), AI-driven threat and hazard detection, and vessel tracking data (AIS), INSURE will provide high-accuracy geo-positioning of threats and hazards, enhancing asset protection, maritime security, emergency preparedness, and societal resilience. The project will leverage advanced AI and machine learning techniques to enable predictive risk assessment and automated intelligent decision support, allowing operators, First Responders (FRs) and security agencies to proactively address threats or hazards. Unlike traditional monitoring solutions, INSURE's long-distance, continuous monitoring capability will transform submarine cables into real-time detection systems, reducing reliance on power-intensive hardware and offshore operations. Through its scalable and cost-effective approach, INSURE will contribute to long-term infrastructure resilience, ensuring secure energy and communication networks, strengthening geopolitical stability, and supporting environmental protection not only in Norway, including the Arctic, but also in other European regions.

The utilization of frequency domain machine learning applications towards developing the Multi-Hazard Early Warning System is the main objective of this position. The frequency domain machine learning applications will be developed by fusing the OptoDAS data that will be collected from the fibre optics cables and AIS data from ocean-going vessels. 

The objective of the Ph.D. position is to develop:

• Development of frequency domain machine learning applications to detect risk or threat situations in underwater infrastructure monitoring
• Develop an approach to geolocate such risk or threat situations
• Fusion of AIS data sets to support the geolocation and identification of the risk or threat-related entities
• Quantification of the performance of frequency domain machine learning applications in underwater infrastructure monitoring 

Want to know more about the position?

For further information about the position, please contact professor Lokukaluge Prasad Perera: 

Qualifications

This position requires a master’s degree or equivalent in Information Technology, Computer Science, Electrical/Electronic Engineering, Automation,  Cybernetics, Physics, Mathematics, Statistics, Nautical Science, Maritime Technology, or a similar field with some sea-going experience and stronger software development experience, and any other requirements. The Master’s degree should be recognized as equivalent to a 2-year Norwegian Master’s degree. The grade for the Master´s degree should be at least a B. If you are near completion of your master’s degree, you may still apply.

The position will contribute to guest lectures and research results for further development of the course portfolio of the program. 

Applicants must document fluency of in English and be able to work in an international environment. Nordic applicants can document their English capabilities by attaching their high school diploma. Working knowledge of Norwegian or a Scandinavian language is also beneficial.

It is preferable if the candidate has knowledge and experience in the following fields:

• Digital signal processing and digital filter design
• Frequency domain analysis and application development experience 
• Maritime operational knowledge & experiences.
• Large Language Model-based application development. 
• Deep Learning techniques, Data Engineering, and Semantic Technologies
• Open-source artificial intelligence, machine learning, statistical estimation methods, software tools, and big-data frameworks.
• Programming languages such as e.g. Python, C++, and LABVIEW.

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. 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 collaboration skills
• Have good communication and interaction with colleagues and students
• Wants to contribute to a good working environment

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 Science and Technology and participate in organized doctoral studies within the employment period.

Admission normally requires:  

In order to gain admission to the programme, the candidate must document sufficient potential for research. The applicant must have a grade point average of C (strong 3.0) or better for the master’s degree, which must contain an independent work. 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

• Involvement in an interesting research project 
• Good career opportunities 
• A good academic environment with dedicated 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 550 800 NOK/year with a 3% yearly increase
• If you have to relocate to Tromsø then the Faculty of Science and Technology may reimburse your moving costs. Further details regarding this matter will be made available if you receive an offer from us.

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

How to apply

Please note that the application will only be assessed based on the information submitted by the application deadline via Jobbnorge. It is therefore important that you include all necessary documents demonstrating your qualifications for the position.

Your application must include: 

• Cover letter explaining your motivation and research interests
• CV
• Diploma for bachelor's and master's degree
• Official transcripts of grades/academic record for bachelor's and master's degree
• Explanation of the grading system for foreign education (Diploma Supplement if available)
• Documentation of English proficiency
• Documentation of proficiency in Norwegian or a Scandinavian language (if available)
• 2-3 references with contact information
• Master’s thesis, and any other academic works

Qualification with a master’s degree is required before commencement in the position. You may still apply if you are in the final stages of the master’s degree, but the master’s thesis must be submitted for evaluation within the application deadline. You must submit the thesis and transcript of grades for the master’s degree with your application.

All documentation to be considered must be in a Scandinavian language or English. Diplomas and transcripts must also be submitted in the original language, if not in English or Scandinavian. If English proficiency is not documented in the application, it must be documented before starting in the position. 

General information 

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 to the 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. 

Assessment 

The applicants will be assessed by an expert committee. The committee's mandate is to undertake an assessment of the applicants' qualifications based on the written material presented by the applicants, and the detailed description draw up for the position. A copy of the assessment report will be sent to all applicants. 

The applicants who are assessed as best qualified will be called to an interview. The interview should among other things, aim to clarify the applicant’s motivation and personal suitability for the position.