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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
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level to capture behavioural and attitudinal insights on urban mobility. To process and analyse these large and complex datasets, we will explore advanced machine learning techniques, including deep
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