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known oncological pathophysiology. LIME (Local Interpretable Model-agnostic Explanations): Generates patient-level attributions, showing clinicians the exact weight and direction of individual lab
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reliable evaluation of individual cell health. The master thesis focuses on the development of a machine learning model for the automatic sorting of used lithium-ion cells based on custom
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. Leverage model embeddings in causal inference pipelines for health effects and adaptation policy evaluation. Work with large, high-dimensional datasets (Medicare claims, census, weather, pollution, and
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Your Job You will develop and evaluate model-based charging and vehicle-to-grid strategies for electric vehicles. Your work will combine battery and battery ageing models with real-world mobility
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different types of experimental data to establish reliable methods for identifying physically meaningful model parameters and assessing model accuracy under dynamic operating conditions. In a later stage
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intersection of machine learning, neuroscience, and computational biology. This role centers on computational neurobiology and the use of modern AI/ML methods to model brain circuits and neural activity. In
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and molecular interactions Exploring model architectures and training approaches, including geometric deep learning, diffusion models, and graph neural networks Preparing and processing biological and
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media governance. We look for a curious, creative and collaborative historian to provide a crucial piece of that puzzle by investigating the contestation of the public media model from below in the long
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equipped with variable‑speed electric machines. The objective of this evaluation is to determine whether the proposed model improves the prediction of additional losses introduced by the manufacturing
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The research in this doctoral opportunity will develop a failure model that can represent the combined effect of surface and bending failures in gears to perform reliable health prognostics. Lack of