Publisher
source

Norwegian Institute of Science and Technology

PhD in AI for Ship Design, Construction and Operation Norwegian University of Science and Technology in Norway

Degree Level

PhD

Field of study

Computer Science

Funding

PhD candidate position at NTNU with gross salary normally NOK 550,800 per annum depending on qualifications and seniority. Employment period is 3 years for the doctoral work. The position is part of the Norwegian Maritime AI Center, which is funded for 2026-2030 and includes approximately 25 doctoral scholarships and some postdoc positions.

Deadline

Expired

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Country

Norway

University

Norwegian Institute of Science and Technology

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Keywords

Computer Science
Mechanical Engineering
Information Technology
Marine Engineering
Artificial Intelligence
Civil Engineering
Digital Twin Technology
Ship Design
Knowledge Representation

About this position

NTNU (Norwegian University of Science and Technology) is advertising a PhD position in AI in Ship Design, Construction and Operation at the Department of Ocean Operations and Civil Engineering in Ålesund, Norway.

The project sits within the Norwegian Maritime AI Center and focuses on how knowledge about ships can be represented across design, construction, and operational phases so that AI methods can use it directly. The research themes include knowledge representation, ontologies, knowledge graphs, graph databases, and possible hybrid approaches for linking vessel data, components, systems, and dependencies. The work is closely connected to the maritime industry and real engineering tasks.

This is a strong fit for applicants interested in computer science, information technology, and maritime engineering applications. The post emphasizes AI-assisted inference, data integration across vessel lifecycles, and practical use cases such as identifying missing information, understanding consequences of design changes, and turning scattered design/operational data into a coherent knowledge base.

Eligibility highlights: a relevant Master's degree in Engineering, Naval Architecture, Computer Science, or equivalent; strong academic results (B or better on NTNU's scale or equivalent); programming and AI-related tool experience; and excellent English communication skills. Master students may apply only if the degree will be completed before starting. Experience with industry, applied research, simulation environments, digital twins, or real-time systems is preferred.

Funding: the position is a salaried PhD candidate appointment at NTNU, normally NOK 550,800 gross per year, for a 3-year period. The center is funded for 2026–2030 and includes doctoral scholarships and postdoc positions.

Application deadline: 23 August 2026. Apply through Jobbnorge.no and submit transcripts, diplomas, CV, thesis copy or draft, a project outline (max 1500 words/4 pages), relevant publications/certificates, and three referees.

Funding details

PhD candidate position at NTNU with gross salary normally NOK 550,800 per annum depending on qualifications and seniority. Employment period is 3 years for the doctoral work. The position is part of the Norwegian Maritime AI Center, which is funded for 2026-2030 and includes approximately 25 doctoral scholarships and some postdoc positions.

What's required

Relevant Master's degree in Engineering, Naval Architecture, Computer Science or equivalent; the degree must correspond to a five-year Norwegian course with 120 credits at master's level. Master students may apply only if the master's degree is completed and documented before starting. Applicants need a strong academic background with an average grade of B or better on NTNU's scale, or an equally good academic foundation if grades are not letter-based. Affinity with programming, AI-related tools, and development of applied computational tools is required. Applicants must meet admission requirements for the Faculty's Doctoral Programme in Engineering and have excellent oral and written English. Practical industry experience, applied research, simulation environments, digital twins, or real-time systems are preferred.

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