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that rely upon interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics. This PhD project falls under Research Thrust RT3
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. Responsibilities and qualifications The nature of this project suggests that you should have a strong interest in the mathematical and theoretical aspects of machine learning. A solid background in mathematics (e.g
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statistics. This position will be placed under Research Thrust 2 which mainly involves mathematical physics. Requirements: The applicants must have documented strong qualifications in functional and spectral
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model checking. You should be well versed in basic statistics and practical programming skills is a must. Knowledge about the inner workings of GenAI would be nice but not necessary. You must have a two
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interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics. This PhD project falls under Research Thrust RT3 on representation
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Expertise (experience in one or more of the following areas is preferred): Mathematical foundations of AI, such as optimization, generalization, and approximation theory Statistical machine learning and its
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of BSc and MSc. Qualifications MSc graduates with a background in either engineering, mathematics, computer science, computer engineering, physics, sustainable energy, electro-chemistry, and related
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of BSc and MSc. Qualifications MSc graduates with a background in either Engineering, Mathematics, Computer Science, Computer Engineering, Physics, Sustainable Energy, Electro-chemistry, and related
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with a master's degree in transportation engineering, mathematics, statistics, computer science or a related discipline. In addition, you should meet the following requirements: Excellent quantitative
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with a background in either engineering, mathematics, computer science, computer engineering, physics, sustainable energy, electro-chemistry, and related disciplines, including hands-on experiences