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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
knowledge of AI-enhanced planning in shipbuilding supply chains. Apply quantitative methodologies, such as simulation, analytical modelling, and AI‑driven techniques, to develop decision support for efficient
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
methodologies, such as simulation, analytical modelling, and AI‑driven techniques, to develop decision support for efficient planning and coordination of production activities in supply chains and generate
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Computer science » Modelling tools Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 Oct 2026 - 23:59 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status
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contribute to aiD by developing trustworthy AI-supported methods for multimarket bidding and decision support in Nordic power markets. The rapid integration of wind power, battery storage, and other flexible
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objective is to develop methods that move beyond correlation-based prediction toward causal reasoning, intervention-aware modelling, and interpretable AI systems. This transition from correlation to causation
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immediate leader will be the Head of Department. About the project The project explores how emerging technologies are reshaping urban planning by positioning humans as critical arbiters of AI-driven methods
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, driven by weather, sea state, maneuvering demands, and onboard consumers, while maintaining safe and stable operation within tight physical and regulatory constraints. This requires integration between
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-based plant. A shipboard reactor must respond to a continuously varying electrical and propulsion load, driven by weather, sea state, maneuvering demands, and onboard consumers, while maintaining safe and
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algorithm that interface with interpolated geotechnical fields to generate adaptive, variable-length stope geometries. Calibrate and validate the developed models using real-world mine data Develop, document
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building sensor data, you will train AI models to recognize abnormal performance patterns, quantify quality-adjusted service life, and autonomously recommend whether a system needs maintenance, recalibration