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Particle Acceleration is looking for a PhD Student (f/m/d) Multimodal Reconstruction of Laser-Electron Accelerator Phase Space using Physics-Informed Deep Learning. Your tasks Understand the physical process
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analysis will focus on building sophisticated Deep Learning models, e.g., Long Short-Term Memory (LSTM) networks, to accurately model DPs over time and predict mood deterioration. The project will implement
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, integrative biology approach that utilizes human pluripotent stem cell based model systems, high throughput functional genomic screening and big data based machine learning, bridging the scales from genetics
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University of Massachusetts Medical School | Worcester, Massachusetts | United States | about 3 hours ago
modeling, causal inference, or deep learning is a plus Excellent communication skills and enthusiasm for collaborative, interdisciplinary research The Garber Lab is part of a vibrant computational and
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for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
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deep learning into practical tools for sustainable urban energy systems, supporting applications in forecasting, system optimization, flexibility management, and resilience analysis. The work will be
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for Artificial Intelligence. https://miai.univ-grenoble-alpes.fr/ Activities Develop and evaluate deep learning tools for MRI fingerprint data Write scientific articles Present results at international conferences
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learns auditory information. Methodologically, the project will explore the integration of information-theoretic decompositions, deep neural architectures, and large language models (LLMs) as powerful
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experience with deep learning frameworks (e.g., PyTorch, TensorFlow). Direct, hands-on experience working with Large Language Models (LLMs) and/or transformer models. Familiarity and experience working with
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap