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make extensive use of low-fidelity simulations which can provide fast but inaccurate solutions depending on the flow complexity. To close this gap, this PhD will explore machine-learning (ML) methods
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, this PhD will explore machine-learning (ML) methods to significantly reduce the turnaround time of SRS, thus enabling their use for industrial design processes. By combining state-of-the-art numerical
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
to anticipate and manage. This PhD will develop a machine learning module to detect early warning signals of positive tipping points from techno-economic data, helping policymakers design adaptive strategies
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
. This PhD will develop a machine learning module to detect early warning signals of positive tipping points from techno-economic data, helping policymakers design adaptive strategies for rapid and
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Are you passionate about hardware security, side-channel analysis and machine learning? Do you want to contribute to research within an international environment? If the answer is yes, please
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Apply now The Faculty of Science, Leiden Institute of Advanced Computer Science,is looking for a: PhD Candidate Human-Centered Interpretable Machine Learning (1.0fte) Project description In recent
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of everyday life. This project aims to change that by developing AI-driven methods to assess wellbeing through video-based sentiment analyses. As a PhD student, you will develop and refine machine learning
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to 1) Object-attribute compositionality to replace exhaustive data requirements with structured concept learning, 2) Bias detection and machine unlearning to identify and mitigate bias and shortcuts
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and scalable. Design and build a technology demonstrator prototype of clinical-testing grade. Collaborate with interdisciplinary teams, including clinicians, engineers, and machine learning (ML) and
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FPGAs, CGRAs, and many Machine Learning accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs/GPUs. Yet, porting and optimizing code