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completed) in Natural Language Processing or a closely related area. Solid knowledge of machine learning, especially deep learning. Experience in model development and/or fine-tuning. A practical mindset
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cardiovascular care. Within the consortium, TU Delft contributes expertise in cardiac mechanics, soft tissue modeling, growth and remodeling, machine learning, and uncertainty-aware model personalization. As a
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towards deep, large-scale analyses of STM evolution and action. The focus will lie on a range of arthropods, molluscs, and chordates, with the aim to uncover universal STM design principles as
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subjects and research areas; Experience with one or more general purpose programming languages, for example Python, and general purpose deep learning frameworks, such as Tensorflow or PyTorch; An interest in
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the use of deep learning techniques to generate realistic heterogeneous material representations and to support stochastic hydro-mechanical simulations Extending existing modelling approaches to include
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executed. In close collaboration with PhD researchers and project partners from TUM and ETH, you will contribute to the development of novel control and learning methods for aerial manipulators and multi
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, subjective user feedback, and environmental data. The research will involve machine learning, human-centred experimentation, real-time comfort prediction, and the integration of intelligent climate control
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, and environmental data. The research will involve machine learning, human-centred experimentation, real-time comfort prediction, and the integration of intelligent climate control systems into vehicle