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Field
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase
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expert knowledge in a reusable format. Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model
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questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
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within LTU’s AIC³ Lab (Automation, Industrial Computing, Communication, and Control Laboratory). Subject description The research subject focuses on an integrated development of network architectures
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hardware modification. The AI will learn and adapt the realms of the combustion modes and fine tune the performance for each while the engine is operated. Self-tuning, adaptive, control algorithms will be
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expert knowledge in a reusable format. Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model
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questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
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, the selected researchers will deal with: Research & Development: Designing, developing, and implementing state-of-the-art machine vision and deep learning algorithms to analyze complex image and sensor data
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, employees, IT infrastructure, specialized training). Second, they may require the use of quantitative models, data analysis, and algorithms, but these applications must also safeguard the data privacy and non
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, and space hardware. This PhD research aims to develop a comprehensive Mode Selection Framework for Reduced Order Modelling (ROM) in Structural Dynamics—using machine learning to build robust