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perception built with machine learning. They will build on the lab’s expertise in deep computational models of the auditory system and in particular on recent work building models of prosthetically enabled
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models: deep learning (4D CNNs, Transformers, RNNs) on fMRI and ECoG data Explanatory AI: Applying machine learning models to guide post-stroke neurorehabilitation Predictive AI: Optimizing deep
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learning applications in biomedical research • Deep learning and predictive modeling • Natural language processing and large language models for biomedical data • Drug response prediction and
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Primary supervisor David Dowe Co-supervisors Ron Firestein Research area Machine Learning The proposed PhD project aims to build a machine learning/deep learning-based decision support system that
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Primary supervisor David Dowe Co-supervisors Ron Firestein Research area Machine Learning The proposed PhD project aims to build a machine learning/deep learning-based decision support system that
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experience in process-based modeling/data analytics/deep learning are preferred. Key Responsibilities: Strong candidates will join or take the lead of one of the following projects: Soil organic carbon
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experience in process-based modeling/data analytics/deep learning are preferred. Key Responsibilities: Strong candidates will join or take the lead of one of the following projects: Soil organic carbon
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Apply now » Internal Research Fellow (PostDoc) in Theory of Deep Learning Job Requisition ID: 20829 Date Posted: 5 August 2026 Closing Date: 2 September 2026 23:59 CET/CEST Publication: External
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expected to have: A doctorate in a Machine-Learning related field A deep knowledge of Control Theory, both classical and deep learning based A solid publication record in top level ML venues such as
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<span lang="en">Universitätsklinikum Hamburg-Eppendorf</span> | Hamburg, Hamburg | Germany | 4 days ago
(2024) and Cell Reports (2026). Lucia Testa works on geometric and topological deep learning, including neural networks on simplicial and cell complexes, with contributions in IEEE Transactions on