Open researcher positions - MAI

Open researcher positions

Open researcher positions

Are you passionate about technology, sustainability, and ships? At the Norwegian Maritime AI Centre (MAI), you can be part of research that transforms how ships are designed, built, operated, and understood by using the power of artificial intelligence.

The future of maritime operations will be more digital, data-driven, and still human-centred. And we need bright minds to make it happen. 

We have up to 30 open PhD and PostDoc positions in the Norwegian Maritime AI Centre. These will be announced at Vacancies at NTNU, on the centre's LinkedIn profile, and on JobbNorge. 

Below are the preliminary themes of the PhD projects:  

  • Safety, testing, and assurance of maritime AI systems (including Explainable AI, XAI)

  • ML-based acceleration of ice modeling and hybrid forecasting of ice conditions

  • AI-infused systems for improved ice mapping and forecasting in Arctic environments

  • Harbour infrastructure structural health monitoring (SHM)

  • AI business models and absorptive capacity in maritime organizations

  • Generic models for AI-ROI (Return on Investment) in maritime value chains

  • Anomaly detection in maritime systems and operations

  • Wave prediction and sea loads; operational power/energy prediction and optimization

  • Human-Machine-AI interaction (WAP, XAI, cognitive support)

  • Cybersecurity risks and trustworthy data sharing for maritime AI development

  • AI-supported ship design 

  • Ship design and ship propulsion system design

  • Maritime traffic models and surveillance (radar-based monitoring and detection)

  • ENC and S-100 data products combined with AI agents

  • Route planning using S-100 data (risk-based routing)

  • Human-machine teaming in maritime operations

  • Agentic AI for smart testing of autonomous navigation systems

  • Predictive maintenance and condition monitoring

  • Radar tracking and ship trajectory prediction

  • Learning-based AI captains for knowledge-driven maritime training (on-board training)

  • Trustworthy autonomous AI captains for maritime simulator and on-board training

  • AI-enhanced planning and logistics in shipbuilding supply chains

  • Shipping data analytics

  • Energy management for zero-emission vessels, including battery monitoring and scheduling

  • Propeller noise and hydrodynamics

  • Certification and recognition of safety levels for autonomous and AI-based systems

  • Maritime large language models (LLMs) and multimodal applications

  • Edge AI and data refinement for maritime applications

  • Foundation models for autonomous control

  • AI-based multi-vessel path planning for USVs operated from remote operations centers

  • Advanced deep learning for high-resolution metocean data

  • Prediction of ship behavior in waves

  • Organisational implications of remote maritime operations

  • Designing for Interactive Team Cognition (ITC) in complex remote operations

  • Competence development and training for USV operators