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Video:
https://youtu.be/Xt-yHCN5QS0About the position
This PhD project focuses on developing novel methods for multi-sensor fusion and representation learning that exploit remote sensing priors - satellite optical and multispectral imagery, synthetic aperture radar (SAR), aerial photogrammetry, and prior bathymetry - to augment what an underwater robot can perceive, localize within, and reason about. The aim is to advance principled cross-modal and cross-scale representation learning for the underwater domain, and to demonstrate that richer, uncertainty-aware environmental models lead to more capable and efficient autonomous underwater surveys.
This PhD project will develop principled methods for fusing these heterogeneous observation streams into coherent, uncertainty-aware environmental representations that an underwater robot can exploit for perception, habitat mapping, and adaptive survey planning. The central scientific challenge is cross-modal and cross-scale representation learning: how to encode geometric, acoustic, optical and environmental observations made at different scales, resolutions, modalities and times into a shared representation that is actionable for an onboard robot. Applications include benthic habitat mapping (cold-water coral reefs, kelp forests, seafloor geology), infrastructure inspection and persistent environmental monitoring. The project will investigate whether and how recent foundation models for earth observation and underwater perception can be adapted and extended to support this multi-modal, cross-scale fusion challenge.
Bridging the information gap between broad-scale remote sensing and close-range underwater robot perception represents one of the most compelling open problems in marine robotics. This PhD project focuses on developing novel methods for multi-sensor fusion and representation learning that exploit remote sensing priors, including satellite optical and multispectral imagery, synthetic aperture radar (SAR), aerial photogrammetry, acoustic bathymetry, synthetic aperture sonar and side-scan sonar, to augment the local sensors that an underwater robot uses to perceive, localize within, and reason about. The aim is to advance principled cross-modal and cross-scale representation learning for the underwater domain, and to demonstrate that richer, uncertainty-aware environmental models lead to more capable and efficient autonomous underwater surveys.
The PhD candidate will be supervised by Professor Oscar Pizarro at the Department of Marine Technology (IMT), and the position is part of the recently funded Norwegian Centre for Embodied AI (NCEI).
About the project
Join a nation-wide team: The Norwegian Centre for Embodied AI (NCEI), one of Norway's six national AI centers, is recruiting outstanding researchers to advance a universal science of embodied intelligence. NCEI brings together leading robotics and AI groups with key partners from industry and the public sector to study how intelligence emerges from the interaction between body, computation, and environment, across flying, ground, and aquatic robot configurations. Our mission is to chart a generalizable path for physical AI and transform how robot morphology and autonomy are co-designed, enabling new generations of systems tailored to their operational environments and missions. Successful candidates will join an international community with world-class facilities and strong collaborations across Norwegian universities, research institutes, industry, public agencies, and leading global institutions. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier.
Duties of the position
- Complete your doctoral education leading to the PhD degree.
- Conduct and publish research of high quality within the framework described above.
- Develop fundamental contributions in multi-sensor fusion and representation learning for underwater robotics, with an emphasis on exploiting remote sensing priors.
- Develop implementable methods for onboard robot perception, localization, and adaptive survey planning.
- Conduct experimental deployments and field evaluation using NTNU's Fjordlab AUVs and other infrastructure with acoustic (MBES, SAS), visual, and hyperspectral sensing payloads.
- Participate in international activities such as conferences and/or research stays abroad.
- Collaborate with other researchers within the department, and across departments at NTNU.
- Supervise master's thesis students related to the project.
Be prepared for changes to your work duties after employment.
Required selection criteria
- You must have a relevant master's degree in marine technology, cybernetics, mechatronics, control systems, computer science or equivalent, with strong training in robotics, computer vision, state estimation, machine learning or statistical signal processing
- Your course of study must correspond to a five-year Norwegian course, where 120 credits have been obtained at master's level. Master students graduating summer 2026 are eligible to apply.
- 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 may be 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 in Engineering
- 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
- Solid theoretical background in robot perception, navigation and mapping.
- Background in one or more of: sensor fusion, probabilistic state estimation, underwater perception, remote sensing image analysis, or 3D reconstruction
- Deep understanding of modern machine learning including foundation models and/or self-supervised representation learning
- Solid programming skills in Python and C++. Experience with ROS2 is a plus
- Experience with simulators for robotics, geospatial data tools and remote sensing processing
- Strong skills in mathematics, excellent capacity for mathematical formalism, and ability to grasp new concepts quickly
- Real-world deployment of robotic systems and fieldwork experience, preferably at sea
Personal characteristics
To complete a doctoral degree (PhD), it is important that you are able to:
- Work independently in a structured way, set goals and make plans to achieve them
- Be scientifically curious, critical, creative and open to new research challenges
- Incorporate feedback, resourcefulness and persistence in solving technical problems
- Be reliable, with the ability to work effectively and proactively as part of a multidisciplinary team
- Communicate clearly in person and in writing
- Present and discuss your research with other professionals
- Work constructively under pressure or in the face of adversity
- Be flexible and open to adjusting the plan for the project as needed
Emphasis will be placed on your personal qualities and your motivation for the subject.
We offer
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 employment as a PhD Candidate, it is a prerequisite that you gain admission to the PhD programme in Engineering within three months of your employment contract start date, and that you participate in an organized doctoral programme throughout the period of employment.
The position is conditional on external funding.
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 proposal for an overall description of research questions, theoretical perspectives, methodological design for the project and progress plan
- 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 Oscar Pizarro, e-mail: Oscar.pizarro@ntnu.no. If you have any questions about the recruitment process, please contact Marit Gjersvold, e-mail: marit.gjersvold@ntnu.no.
Application deadline: 24.06.2026
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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.