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Field
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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platform. Initially, a black box deep learning approach will be implemented. However, due to the need for robustness, transparency, and explainability (e.g. for quality control across sectors), the research
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and accuracy, ultimately saving lives. This collaborative PhD project aims to develop and evaluate advanced deep learning models for speech and audio analysis to predict Category 1 emergencies
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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informatics, biomedical engineering, statistics, or related fields. The lab is engaged in developing novel deep learning and AI-based technologies for digital biopsies from medical images and real-world
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deep learning and scalable deployment Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run experiments using the latest
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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communication skills an early career researcher with publication record, presentation skills and commitment to research integrity equipped with excellent software skills and hands-on experience with deep learning
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Generative Models" (UCL , Oxford, Imperial, Edinburgh, Cardiff, Manchester and Surrey) and with its industrial partners. Key responsibilities include working on deep learning, probabilistic modelling, deep