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Field
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assessment. Design and train reinforcement learning agents to optimize operational safety. Build and validate dynamic Bayesian network models integrating empirical and synthetic data. Conduct scenario-based
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cases: Logistics, shipping and business transactions; Ship design and construction; Voyage planning and optimization; Condition monitoring and maintenance; Crew training; Maritime traffic and ship
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, user training, scheduling, and service coordination. Development of Standard Operating Procedures (SOPs) and quality-control workflows. Maintenance and troubleshooting of core instrumentation. Instrument
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protocols to our Workflow Performing microscopy experiments on sperm dynamics under various controlled environmental conditions. Merging experimental results, simulations, and literature for optimal
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, scalability, and adaptability to various applications such as autonomous systems, IoT devices, and wearable technologies. Research Focus Areas: 1- Neuromorphic and AI-Optimized Processors: Design AI-specific
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area of power systems with special interest in power system controls, protection, optimization, and AI/ML applications in power and energy systems. Experience with experiments and hardware-in-the-loop is
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in Python and R for data analysis, modeling, and visualization. Proficiency in building efficient pipelines that use optimized software to process large datasets. Proficiency in supervised
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, differential equations, geometry/topology, numerical analysis, optimization, and statistics. Part of the research is also carried out in close cooperation with other fields of science and technology at NTNU, as
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of precision fermentation or cell culture - Affinity towards technical tasks and bioprocess control - Advantageous: Experience in mathematic modeling, programming, CAD, microfluidic or bioreactor systems