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manufacturer and technology company. Applications are invited for a 3.5-year EPSRC funded UDLA PhD studentship. The studentship will start on 1st October 2026. Project Description As Deep Learning and
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latent coordinates; ii) Cross-modal alignment (e.g., canonical correlation analysis and Deep CCA) to align heterogeneous parameterizations and modalities in a shared latent space, iii) Operator learning
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environment. Key research Objectives: AI Innovation (Taxonomic Identification): Developing and optimizing deep-learning architectures (e.g., YOLO) for the automated detection and classification of nocturnal
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using existing NPL datasets. The work will integrate suitable physics-based models (for example PV performance modelling, electro-thermal and thermofluid dynamics) with deep learning and multi-fidelity
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interdisciplinary team with clinicians and engineers; You have strong programming skills in Python; You have knowledge of medical image processing, and machine learning and deep learning techniques; Written and
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 1 month ago
General Summary of the Position Postdoctoral positions in Deep-Learning Omics are available in the Zhou Lab (https://profiles.umassmed.edu/display/20062865 ). The Zhou Lab at UMass Chan Medical
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multimodal data. Your responsibilities include: Developing and applying machine learning, deep learning, and LLM-based methods to multimodal clinical datasets e.g. EHR, imaging, omics, sensor data Designing
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. Melodia, SIA: Symbolic Interpretability for Anticipatory Deep Reinforcement Learning in Network Control, IEEE INFOCOM 2026 [3] A. Duttagupta, M. Jabbari, C. Fiandrino, M. Fiore, J. Widmer, SymbXRL: Symbolic
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| Bioacoustics | Precision Livestock Farming | Artificial Intelligence | Machine Learning | Deep Learning | Animal Behaviour | Acoustic Biomarkers | Sustainable Agriculture | Digital Farming View All Vacancies
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open to candidates with a strong interest in either: i) Radio/physical-layer intelligence (e.g., channel estimation, CSI prediction, edge-deployable deep learning), or ii) Networking and control-plane