This is NTNU

NTNU is a broad-based university with a technical-scientific profile and a focus in professional education. The university is located in three cities with headquarters in Trondheim.

At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world.

You will find more information about working at NTNU and the application process here.

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About the position

Are you motivated to take a step towards a doctorate and open up exciting career opportunities? As a PhD Candidate with us, you will work to achieve your doctorate, and at the same time gain valuable experience that qualifies you for a further career in higher education and research, in and outside academia.

We invite applications for a PhD position funded by NTNU and associated with the Norwegian Maritime AI Center (MAI). The position contributes to Use Case 12 (UC12): Arctic Maritime Operations and addresses a key challenge for maritime AI: supporting safe, reliable, and timely operational decisions in ice‑affected waters under high uncertainty.

The PhD will focus on the Marginal Ice Zone (MIZ), where sea ice responds rapidly to wind, waves, and currents, and where existing ice charts and satellite products are often insufficient for short‑term operational planning. The project will develop AI‑enabled and physics‑informed forecasting and decision‑support approaches by combining heterogeneous observations with physics‑based simulation tools, including operationally adapted configurations of the SAMS (Simulation of Arctic Marine Systems) framework.

Your immediate leader will be a professor.

About the project

The Marginal Ice Zone represents one of the most complex and operationally challenging environments in Arctic maritime operations. In the MIZ, wave–ice interaction, ice breakup, and subsequent compaction can rapidly alter navigability. Storm events may lead to fast shifts in the ice edge and sudden extension of the MIZ, requiring timely decisions under significant uncertainty.

While satellite observations and ice charts are essential sources of information, their temporal resolution and predictive capability are often insufficient in the MIZ. This motivates the development of short‑term forecasting and scenario‑based tools that explicitly account for fast ice dynamics and uncertainty relevant for operational planning.

The PhD addresses Arctic ice navigation as a system‑level challenge, integrating heterogeneous information from onboard sensors such as marine radar and cameras, satellite Earth‑observation products, ice charts, and metocean forecasts. The objective is to produce coherent, continuously updated representations of ice conditions that support short‑term forecasting, nowcasting, and scenario exploration for route planning and operational decision‑making.

Physics‑based simulation plays a central role in this research project by enabling propagation of ice conditions in time and exploration of physically plausible scenarios when observations are sparse or delayed. In this project, the SAMS framework will be used in an operationally oriented configuration, focusing on computationally efficient simulation of MIZ processes such as wave‑induced ice breakup and ice‑edge evolution.

These simulations will both directly inform forecasting and be used to support AI model training, validation, and interpretability, providing a physically grounded backbone for hybrid AI–physics decision‑support concepts.

AI methods will be applied to fuse heterogeneous data sources, learn fast surrogate representations of physics‑based simulations, and quantify uncertainty relevant for operational decisions. The project leverages MAI foundations for AI‑ready data, hybrid modelling, and trusted AI, while tailoring these capabilities to Arctic MIZ conditions.

The research will be guided by operationally relevant questions, such as how storms and wave forcing affect short‑term MIZ evolution; under what conditions wave–ice interaction leads to rapid ice breakup or MIZ extension; and how hybrid AI–physics approaches can support dynamic route planning with quantified uncertainty. Emphasis will be placed on time horizons from minutes to days, which are most relevant for maritime operations.

Expected outcomes include hybrid AI–physics workflows for MIZ forecasting, AI‑ready datasets derived from observations and simulations, prototype forecasting and scenario‑evaluation components, and contributions to decision‑support concepts compatible with S‑100‑based maritime information products. The work will result in scientific publications and demonstrators aligned with MAI objectives.

The PhD will be conducted in close collaboration between NTNU and the Norwegian Meteorological Institute (MET), with active involvement of interested MAI’s user partners such as Equinor and the Norwegian Coastal Administration (NCA). This ensures close alignment between research outcomes, operational needs, and regulatory frameworks.

We seek a motivated candidate with a background in engineering, ocean technology, computer science, data science, geophysics, or related discipline, and with a strong interest in AI, modelling, and Arctic maritime operations. Experience with numerical modelling, geospatial data, or machine learning is an advantage. An interest in system‑level thinking and integration of models, data, and AI methods is particularly valued.

The appointment will be carried out in accordance with the principles of the State Employees Act and applicable export control regulations governing the transfer of knowledge, technology, and services. Candidates whose background is assessed to be in conflict with these regulations cannot be employed.

Duties of the position

Be prepared for changes to your work duties after employment.

Required selection criteria

You must have a relevant Master's degree in engineering, ocean technology, computer science, data science, geophysics or equivalent. Your education must correspond to a five-year Norwegian course, where 120 credits have been obtained at master's level. Master students can apply, but the master's degree must be obtained and documented before starting the position.
You must have a strong 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 grade background, you maybe considered if you can document that you are particularly suitable for a PhD education.
You must meet the requirements for admission to the faculty's Doctoral Programme
Good oral and written presentation skills in English

PLEASE NOTE: For detailed information about what the application must contain, see paragraph “About the application”.

The appointment is to be made in accordance with NTNUs guidelines for recruitment positions for general criteria for the position.

Preferred selection criteria

Strong interest in AI, modelling, and Arctic maritime operations.
Experience with numerical modelling, geospatial data, or machine learning.
An interest in system‑level thinking and integration of models, data, and AI methods.
Experience with high-performance computing
Interest in interdisciplinary research
Good oral and written presentation skills in Norwegian

Personal characteristics

To complete a doctoral degree (PhD), it is important that you are able to:

Strong motivation for research
Ability to work independently and collaboratively
Show curiosity and strong motivation for the subject
Present and discuss your research with other professionals
Get involved and contribute constructively with feedback
Demonstrate strong communication skills

Emphasis will be placed on personal qualities.

We offer

Evaluate and remove/add what is relevant for the position.

An exciting job with an important mission in society
Developing tasks in a strong and international professional environment
Career guidance and follow-up during the PhD period
Open and inclusive working environment with committed colleagues
Working capital that can be used to implement the project
Mentor programme as a new employee at NTNU
Favorable terms as a member of the Norwegian Public Service Pension Fund (SPK)
Free Norwegian language training at a basic level (A2)

As a PhD Candidate at NTNU, you will have access to employee benefits.

Diversity

Diversity is a strength, and at NTNU we aim to be an employer that reflects the diversity in society and that makes use of the potential of the population's collective skills. Our vision is Knowledge for a better world and our values are creative, critical, constructive and respectful. We believe that an organization that is equal, diverse and gender-balanced is essential for us to achieve our goals.

We strive to attract employees with different skills, life experiences and perspectives to contribute to even better problem solving of our societal mission in research and education.

If you think this position is relevant and interesting, we encourage you to apply, regardless of gender, functional ability and cultural background, or whether you have been out of work for a period of time.

At NTNU we want to increase the proportion of women in scientific positions. We have a number of measures to promote equality.

Salary and conditions

In the position of PhD Candidate, code 1017, your gross salary will normally be NOK 550 800,-per annum depending on qualifications and seniority. A 2% statutory contribution to the State Pension Fund is deducted from the salary.

The employment period is 3 years for the doctoral work in addition to 1 year of career promotion work. (A minimum of three work years of the total term period must be dedicated to doctoral work.)

For employment as a PhD Candidate, it is a prerequisite that you gain admission to the PhD programme in Civil and Environmental Engineering within three months of your employment contract start date, and that you participate in an organized doctoral programme through out the period of employment.

As an employee at NTNU, it is important that you keep yourself up to date with academic and organizational changes and adapt to them.

For the necessary professional and social interaction, it is a prerequisite that you are physically present and available to the institution on a daily basis.

The appointment is carried out in accordance with the principles of the State Employees Act, and Export control (legislation that regulates the export of knowledge, technology and services). Candidates who, after assessment of the application and attachments, are considered to bein conflict with the criteria in the latter act, will not be able to be employed.

About the application

The attachments (including a description of your scientific work) must accompany the application as these documents form the basis of the application assessment. The documents must be in Norwegian/a Scandinavian language or English.

Please note: the application will only be assessed on the basis of the information we have received by the application deadline. Therefore, make sure that your application clearly shows how your skills and experience meet the criteria described above. The application and all attachments must be sent electronically via Jobbnorge.no. If you are invited to an interview, you must bring certified copies of certificates and diplomas upon request.

The application must include:

Transcripts and diplomas for Bachelor's and Master's degrees
CV
Copy of Master's thesis. If you have recently submitted your Master's thesis, you can attach a draft of the thesis. Documentation of a completed Master's degree must be presented before taking up the position.
Project outline containing proposals for an overall description of research questions, theoretical perspectives, methodological design for the project and progress plan (maximum 1500 words/4 pages)
Short letter of motivation (400 words/1 page)
Possibly publications etc. other relevant research work
Possibly certificates
Names and contact information of three relevant referees

If all, or parts, of your education has been taken abroad, we also ask you to attach documentation of the scope and quality of your entire education, both Bachelor's and Master's education, in addition to other higher education. If your institution uses “diploma supplement” (normal for most European institutions), you must attach this. A description of the documentation required can also be found here. If you already have a statement from Norwegian Directorate for Higher Education and Skills (HK-dir), please attach this as well.

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

When assessing the best qualified, we emphasize necessary qualifications such as education, experience and personal suitability. Motivation for the position, ambitions, and potential for research will also count when assessing the candidates.

NTNU recognizes a wide range of academic contributions and has committed itself to The San Francisco Declaration on Research Assessment and CoARA (responsible assessment of research and recognition of a greater breadth of academic contributions in accordance with NTNU's social mission).

General information

A public list of applicants with name, age, job title and municipality of residence is prepared after the application deadline. If you wish to be exempt from entry on the public applicant list, this must be justified. Assessment will be made in accordance with current legislation. You will be notified if the exemption is not granted.

If you think this position looks interesting and in line with your qualifications, you are welcome to apply.

If you have any questions about the position, please contact Professor Raed Lubbad, telephone +47 73 59 45 83, e-mail: raed.lubbad@ntnu.no.

If you have any questions about the recruitment process, please contact HR Consultant Oda Aune, e-mail: oda.aune@ntnu.no.

Application deadline: 23.28.2026

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For practical information about working at NTNU, please visit this webpage.

The city of Trondheim is a modern European city with a rich cultural scene. Trondheim is the tech 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.

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