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further developed and supplemented by additional image-processing algorithms for studying liquid flow in real time. Development of experimental design and test rigs. Evaluation of accuracy in measurement
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, optimization algorithms, and machine learning techniques to tackle this challenging, interdisciplinary problem. As a PhD candidate with us, you will work to achieve your doctorate, and at the same time gain
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selection criteria You must have a relevant background in algorithms and/or database systems with a research-oriented master’s thesis. Good programming skills. Good written and oral English language skills
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techniques for effective analysis of massive-size geophysical data. The goal is to develop algorithms for classification and predictions that enable early warning systems in various geosciences applications
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Sustainable Energy AS. Duties of the position The technical work tasks concern: Development of smart algorithms and modules for load prediction and minimization of fuel, energy, and emissions for marine vessels
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aspects such as materials, process safety, sustainability and circularity, and employ innovative design approaches and modelling techniques such as optimization algorithms. Specifically, your study will
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, and employ innovative design approaches and modelling techniques such as optimization algorithms. Specifically, your study will involve: Thermal Insulation Behaviour: The research will model how thermal
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. Knowledge Graphs based on engine propeller combinator diagrams of the same vessels. Machine learning algorithms for data clustering and regressions of ship performance and navigation data sets as a part of
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with algorithms, numerical methods, signal processing and dynamic system modeling Experience from or formal training within analysis and processing of large data sets, signal processing is mandatory
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regarding these systems. Your research will delve into developing complex AI algorithms with robust fault tolerance capabilities to maintain system stability and safety under non-standard conditions. The