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solutions, the center will address a diverse and impactful set of use cases: Logistics, shipping and business transactions; Ship design and construction; Voyage planning and optimization; Condition monitoring
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set of use cases: Logistics, shipping and business transactions; Ship design and construction; Voyage planning and optimization; Condition monitoring and maintenance; Crew training; Maritime traffic and
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, e.g. in Python, particularly for machine learning Experience with machine learning theory, evaluation metrics, algorithmic fairness, statistics, or optimization is an advantage Language requirement
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transactions; Ship design and construction; Voyage planning and optimization; Condition monitoring and maintenance; Crew training; Maritime traffic and ship surveillance; Decarbonization and energy management
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
transactions; Ship design and construction; Voyage planning and optimization; Condition monitoring and maintenance; Crew training; Maritime traffic and ship surveillance; Decarbonization and energy management
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ecosystems where interconnected multi-agents interact strategically in dynamic and uncertain environments. While Artificial Intelligence (AI) optimizes predictions or policies, energy systems are inherently
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theory, algorithms, and experiments on multimode mechanical quantum platforms (circuit quantum acoustodynamics with transmon–HBAR devices; HBAR arrays; microwave optomechanics). The postdoc will work
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
prototype maritime AI solutions, the center will address a diverse and impactful set of use cases: Logistics, shipping and business transactions; Ship design and construction; Voyage planning and optimization
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dynamic and uncertain environments. While Artificial Intelligence (AI) optimizes predictions or policies, energy systems are inherently multi-agent, strategic, and resource-constrained. Each agent has its
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partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML Enhancement of AI/ML with in-network computing & processing Adaptation & optimization