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climate. The doctoral researcher will be working on the AI-Dream project. They will have to develop criteria and evaluation suites to test the “physical” accuracy of deep Machine Learning (ML) models
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skills in English (written and spoken). Programming skills and experience with deep learning frameworks (PyTorch, Hugging Face, etc.). Qualification requirements The eligibility criteria for prospective
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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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Proven experience with deep learning frameworks such as PyTorch, and familiarity with multimodal data fusion is highly desirable Ability to work independently, as well as collaboratively in
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Proficiency in Python and experience working in Linux-based HPC environments or cloud computing platforms Proven experience with deep learning frameworks such as PyTorch, and familiarity with multimodal data
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criteria and evaluation suites to test the “physical” accuracy of deep Machine Learning (ML) models. The doctoral researcher will also use state-of-the-art methods to make the ML models explainable, namely
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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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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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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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of Engineering drives science and innovation in industrial and built environment technologies. We are committed to educating a new generation of experts who combine technical excellence with a deep understanding