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academia and industry. Requirements The following qualifications are required: Solid knowledge in mathematics and statistics, in areas such as linear algebra, probability theory, machine learning, high
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and verbal communication skills in English Experience in some of the following areas is meritorious: group theory, statistics, neural networks, machine learning and programming. Evidence of problem
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-efficient built environment. You will be supported by leading researchers at the Department of Architecture and Civil Engineering and partners from the Digital Twin City Centre , funded by Sweden's
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dynamics simulation and controls toolbox fascinating? The research of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial
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, engineering physics, biomedicine, or similar Documented skills in data-driven analysis (machine learning using python with TensorFlow, PyTorch, or similar) and computational statistics Specific knowledge of big
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machine learning, engineering, data sciences, applied mathematics, or another related field; or Have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including
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machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid understanding of fluid dynamics and heat transfer, as
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. Requirements To meet the entry requirements for doctoral studies, you must hold a Master’s (second-cycle) degree inengineering physics, electrical engineering, machine learning, data science, computer
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of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial intelligence in general. The focus is broadly upon the development
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using machine learning”. The main task of the doctoral student is to carry out an individual research project under supervision. The doctoral position will contribute important expertise in data analysis