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this position, you will have a chance to make an impact by helping translate state-of-the-art research into a technology with strong commercial potential in the deep-tech sector. Join us in shaping the future
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experimental and operational machinery datasets, including preprocessing, feature representation, uncertainty quantification and model validation. Investigating latent-variable, deep-learning and Bayesian
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preprocessing, feature representation, uncertainty quantification and model validation. Investigating latent-variable, deep-learning and Bayesian approaches for learning informative health-state representations
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scientific writing and academic publishing Programming skills and experience with MATLAB, Python, or similar tools Familiarity with machine learning and deep learning methods Applicants must fulfill
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, Python, or similar tools Familiarity with machine learning and deep learning methods Applicants must fulfill the eligibility and admission criteria for Aalto’s Doctoral Programme in Engineering as
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experts who combine technical excellence with a deep understanding of sustainable development in shaping societies. Our research focuses on sustainable built environment, mechanics and materials
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technologies. We are committed to educating a new generation of experts who combine technical excellence with a deep understanding of sustainable development in shaping societies. Our research focuses
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and built environment technologies. We are committed to educating a new generation of experts who combine technical excellence with a deep understanding of sustainable development in shaping societies
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are committed to educating a new generation of experts who combine technical excellence with a deep understanding of sustainable development in shaping societies. Our research focuses on sustainable built
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technical excellence with a deep understanding of sustainable development in shaping societies. Our research focuses on sustainable built environment, mechanics and materials, multidisciplinary energy