The position

The PhD positions are based in [AI]² - The Arctic Institute for AI - at UiT The Arctic University of Norway.

[AI]², hosted by the Faculty of Science and Technology, is UiT’s new strategic flagship initative for interdiciplinary AI research and research-based innovation for meeting the major societal challenges of our time facing the Arctic, Europe and the World.
The positions will also be associated with the Visual Intelligence Research Centre and will be formally embedded in the UiT Machine Learning Group at the Department of Physics and Technology.

The positions are for a period of three years. The objective of the positions 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 the commencement of the position.

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

Place of work

[AI]² is a new strategic AI research initiative at UiT. Our mission is to contribute solutions to the societal challenges facing Europe and the world, particularly in the Arctic, a strategic frontier where environmental change, geopolitical competition, and emerging technologies are reshaping security dynamics. Important strategic focus areas for these positions are to develop solutions for increased preparedness and situational awareness leveraging satellites and UAVs, for climate and environmental forecasting and change, and for asset and infrastructure monitoring. We do this with “eallju” (Sami: eagerness to work) on a foundation of fundamental AI research in artificial neural networks and deep learning.

[AI]² is partially growing out of Visual Intelligence (VI), hosted by UiT as a Centre for Research-based Innovation (SFI) in AI funded for 8 years by the Research Council of Norway (grant no. 309439). The positions will be associated with VI to benefit from that research environment. In VI, the central topic is deep learning for industry innovation in the Earth, marine, energy and health sectors by developing novel methodology for learning from limited data, for uncertainty quantification, for incorporating context and dependencies, and for developing interpretable AI.

The UiT campus in Tromsø is located near the city centre. Tromsø is a vibrant city located in Northern Norway, with just shy of 80 000 inhabitants, surrounded by the stunning landscape of Northern Scandinavia. The location also offers ample opportunities for, e.g., sighting the northern lights, midnight sun, hiking and skiing.

The position's field of research

As an [AI]² researcher, you will contribute to solving the pressing societal challenges of our time for a sustainable future. This means that the main aim is not to develop a favorite “AI hammer” for then to look for problems this tool may help solve. Rather, the aim is to identify particularly important problems to solve, for then to contribute to the development of particularly promising AI methodology suited for helping provide solutions for these real world problems and with real world stakeholders involved.

However, when developing the next generation AI technology, non-negotiable objectives are for the technology itself to be resilient, robust, and reliable, which are the hallmarks of responsible AI.

We are announcing up to 5 PhD positions. The intended thematic application areas for the positions are as follows:

1. 2-3 positions at the intersection of microclimate modeling and forecasting. Microclimate modeling refers to modeling of wind fields or other atmospheric or Earth surface variables at unprecedented temporal and spatial resolution. This is important for aviation and for autonomous operation of UAVs (unmanned aerial vehicles), e.g. in a search and rescue context. At least one position will be conducted in close collaboration with the aviation and drone group at UiT. Forecasting refers to prediction at short range, medium range or long range (e.g. decadal) of e.g., sea ice in the Arctic or other phenomena that depend on the changing weather and
Generert fra Jobbnorge.no tirsdag 27. mai 2025 kl. 16:00 Side 2 / 5
climate. It is also important for early warning systems, for instance, related to climate-induced extreme events, to help enable resilient societies for the future.

2. 1-2 positions at the intersection of situational awareness over sea and land and in the oceans by analysis of data from spaceborne satellites, UVAs, other observational measurements such as ocean echosounders or sensors at UUVs (unmanned underwater vehicles). Important challenges include, e.g., ship detection and monitoring, pollution and oil spill detection, and detection of situational anomalies in general.

3. 1 position related to infrastructure monitoring. AI-powered infrastructure monitoring helps organizations detect anomalies, predict failures, and resolve issues before they impact users or services.

For all positions, fundamental and methodological AI research underpins the development, with overarching objectives centered on:

Resilient AI: Develop AI technology that is resilient to changes and unforeseen events or attacks.
Robust AI: AI that is resistant to variations, operating conditions, and drifts.
Reliable AI: Interpretable AI for users, which is energy-efficient and aligned with fundamental human values.

Potential underlying research directions to develop within these thematic areas and objectives are

Develop novel AI methodology which leverages numerical solvers (e,g for physical systems governed by partial differential equations) and which respects physical laws.
Represent the general properties of relevant and real-world data by self-supervised learning towards AI foundation models.
Represent general properties of data coming from different sources, i.e., multimodal AI models (combining images, text, etc).
Understand the important mechanisms of the AI models in terms of their prototypical behaviour, individual neurons or layers within networks, or the quality of the data (data-centric intelligence).
Develop interpretable generative AI solutions.
Develop a new methodology to improve calibration and uncertainty quantification.

Important

We expect all PhD positions to operate as a batch and to communicate and collaborate as a group. You must indicate in prioritized order the thematic application areas you are interested in.
A detailed work plan and project description for the PhD candidate will be devised in collaboration between the fellow, the research team and the supervisors, as well as interdisciplinary collaborators.

Want to know more about the position?

For enquiries about the position, please contact:

Director of [AI]² and Visual Intelligence, Professor Robert Jenssen: robert.jenssen@uit.no
Co-Directors of [AI]² and Principal Investigators at Visual Intelligence
o Associate Professor Elisabeth Wetzer: elisabeth.wetzer@uit.no
o Professor Georgios Leontidis: georgios.leontidis@uit.no
Principal Investigators
o Professor Michael Kampffmeyer: michael.kampffmeyer@uit.no
o Associate Professor Kristoffer Wickstrøm: kristoffer.k.wickstrom@uit.no
o Associate Professor Qing Liu: qing.liu@uit.no
Head of Department of Physics and Technology, Professor Olav Gaute Hellesø: olav.gaute.helleso@uit.no.

Your role as a PhD Fellow

You will be a part of [AI]². You will also be part of Visual Intelligence, and you will be formally embedded in the UiT Machine Learning Group. The [AI]² is in a build-up phase, but grows partially out of the Visual Intelligence Centre. For that reason, you will be part of the Visual Intelligence Graduate School (VIGS), a vibrant community of early career researchers within the centre. You will engage in collaborative research with the other members of [AI]² towards research-based innovation. You will invest considerable time and effort in interdisciplinary collaboration with researchers who are not machine learning experts but domain experts within the application field of your position.

You will be expected to actively collaborate outside of core machine learning with stakeholders, and for that reason, interest and experience with interdisciplinary research and innovation from a foundation of fundamental AI research will be considered positively. You are expected to contribute to [AI]² (including VI’s) virtual and physical seminars, be open to interdisciplinary collaboration and participate in data gathering and processing when needed. [AI]² and VI host the conference NLDL (Northern Lights Deep Learning Conference http://nldl.org) and you are expected to be involved in the organization.

Qualifications

We are particularly seeking candidates with a solid background in machine learning methodology, in terms of the mathematical and statistical foundation of such methods. We are seeking candidates with coursework and experience in deep learning, neural networks and machine learning, e.g. self-supervised learning, convolutional neural networks, transformer-based networks, statistical and information theoretic learning, geometric learning, Bayesian learning, (implicit) neural representations, neural operator learning.

Required qualifications:

You must hold a Master’s degree in machine learning or related fields within e.g., mathematics, statistics, computer science, physics, electrical engineering.
A strong formal course background in deep learning and machine learning in general or relevant topics such as pattern recognition or computational statistics is required. Important topics are described above.
Documented programming skills, for example, using Python, etc.
Good communication skills in English are necessary and documented fluency in English is required. Nordic applicants can document their English capabilities by attaching their high school diploma.

Preferred qualifications:

Research experience via a Master thesis, internships or similar involving the development of deep learning and machine learning methodology and applications.
Experience with software tools such as e.g. PyTorch, Keras, Tensorflow, and Jax.
Experience with collaborative coding, e.g. via Git/GitHub.

Desired qualifications:

Experience in interdisciplinary and collaborative research, given that all positions aim for innovation and collaboration.
Any relevant scientific publications.
Abilities to be creative and be able to take on and develop own initiatives.

We will also emphasize motivation and personal suitability for the position. We are looking for interested, active and highly motivated candidates, who like to explore new technologies, are both independent thinking and enjoy working in collaboration with others. We hope this is you!

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:

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

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

The possibility to make a difference, help solve societal challenges and be at the forefront of AI and deep learning research
An internationally leading and welcoming academic environment with dedicated colleagues Good career opportunities
A large degree of independence in work
Good career opportunities
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:

Qualification with a master’s degree is required before commencement in the position. If you are near completion of your master’s degree, you may still apply and submit a draft version of the thesis and a statement from your supervisor or institution indicating when the degree will be obtained. You must still submit your transcript of grades for the master’s degree with your application.

All documentation to be considered must be in a Scandinavian language or English. 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.

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